Training in progress, step 10
Browse files- README.md +59 -0
- adapter_config.json +32 -0
- adapter_model.safetensors +3 -0
- runs/Jan07_11-26-45_371ca9b7a7c7/events.out.tfevents.1704626819.371ca9b7a7c7.476.0 +3 -0
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- runs/Mar21_01-53-07_d72aea89d4b6/events.out.tfevents.1710986084.d72aea89d4b6.3894.0 +3 -0
- runs/Mar22_04-33-33_6b98cdd15d10/events.out.tfevents.1711082034.6b98cdd15d10.209.0 +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
- training_args.bin +3 -0
- wandb/debug-cli.root.log +0 -0
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- wandb/run-20240107_113444-ebd79hle/files/output.log +452 -0
- wandb/run-20240107_113444-ebd79hle/files/requirements.txt +497 -0
- wandb/run-20240107_113444-ebd79hle/files/wandb-metadata.json +52 -0
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- wandb/run-20240107_113444-ebd79hle/run-ebd79hle.wandb +0 -0
- wandb/run-20240321_015458-y11xrjxv/files/config.yaml +678 -0
- wandb/run-20240321_015458-y11xrjxv/files/output.log +81 -0
- wandb/run-20240321_015458-y11xrjxv/files/requirements.txt +510 -0
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- wandb/run-20240322_043407-hize5f4p/run-hize5f4p.wandb +0 -0
README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- trl
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- sft
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- generated_from_trainer
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base_model: mistralai/Mistral-7B-v0.1
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model-index:
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- name: Mistral-7B-Finetuning-Insurance
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Mistral-7B-Finetuning-Insurance
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.03
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- training_steps: 60
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### Training results
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### Framework versions
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- PEFT 0.9.1.dev0
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- Transformers 4.39.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"loftq_config": {},
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"lora_dropout": 0.05,
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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special_tokens_map.json
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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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2024-03-22 04:37:43,204 DEBUG SenderThread:4275 [sender.py:send():378] send: stats
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2024-03-22 04:37:56,975 DEBUG HandlerThread:4275 [handler.py:handle_request():146] handle_request: status_report
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wandb/debug.log
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+
2024-03-22 04:34:07,548 INFO MainThread:209 [wandb_setup.py:_flush():76] Current SDK version is 0.16.4
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2024-03-22 04:34:07,550 INFO MainThread:209 [wandb_setup.py:_flush():76] Configure stats pid to 209
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2024-03-22 04:34:07,551 INFO MainThread:209 [wandb_setup.py:_flush():76] Loading settings from /root/.config/wandb/settings
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2024-03-22 04:34:07,551 INFO MainThread:209 [wandb_setup.py:_flush():76] Loading settings from /content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/wandb/settings
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2024-03-22 04:34:07,551 INFO MainThread:209 [wandb_setup.py:_flush():76] Loading settings from environment variables: {}
|
6 |
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2024-03-22 04:34:07,552 INFO MainThread:209 [wandb_setup.py:_flush():76] Applying setup settings: {'_disable_service': False}
|
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2024-03-22 04:34:07,553 INFO MainThread:209 [wandb_setup.py:_flush():76] Inferring run settings from compute environment: {'program': '<python with no main file>'}
|
8 |
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2024-03-22 04:34:07,553 INFO MainThread:209 [wandb_setup.py:_flush():76] Applying login settings: {'api_key': '***REDACTED***'}
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9 |
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2024-03-22 04:34:07,553 INFO MainThread:209 [wandb_init.py:_log_setup():526] Logging user logs to /content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/wandb/run-20240322_043407-hize5f4p/logs/debug.log
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10 |
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2024-03-22 04:34:07,554 INFO MainThread:209 [wandb_init.py:_log_setup():527] Logging internal logs to /content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/wandb/run-20240322_043407-hize5f4p/logs/debug-internal.log
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2024-03-22 04:34:07,554 INFO MainThread:209 [wandb_init.py:_jupyter_setup():472] configuring jupyter hooks <wandb.sdk.wandb_init._WandbInit object at 0x7f0538e72f80>
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2024-03-22 04:34:07,555 INFO MainThread:209 [wandb_init.py:init():566] calling init triggers
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2024-03-22 04:34:07,555 INFO MainThread:209 [wandb_init.py:init():573] wandb.init called with sweep_config: {}
|
14 |
+
config: {}
|
15 |
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2024-03-22 04:34:07,555 INFO MainThread:209 [wandb_init.py:init():616] starting backend
|
16 |
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2024-03-22 04:34:07,555 INFO MainThread:209 [wandb_init.py:init():620] setting up manager
|
17 |
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2024-03-22 04:34:07,561 INFO MainThread:209 [backend.py:_multiprocessing_setup():105] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
18 |
+
2024-03-22 04:34:07,564 INFO MainThread:209 [wandb_init.py:init():628] backend started and connected
|
19 |
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2024-03-22 04:34:07,592 INFO MainThread:209 [wandb_run.py:_label_probe_notebook():1295] probe notebook
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20 |
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2024-03-22 04:34:12,608 INFO MainThread:209 [wandb_run.py:_label_probe_notebook():1305] Unable to probe notebook: 'NoneType' object has no attribute 'get'
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21 |
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2024-03-22 04:34:12,608 INFO MainThread:209 [wandb_init.py:init():720] updated telemetry
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22 |
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2024-03-22 04:34:12,615 INFO MainThread:209 [wandb_init.py:init():753] communicating run to backend with 90.0 second timeout
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23 |
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2024-03-22 04:34:13,063 INFO MainThread:209 [wandb_run.py:_on_init():2262] communicating current version
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24 |
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2024-03-22 04:34:13,171 INFO MainThread:209 [wandb_run.py:_on_init():2271] got version response
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25 |
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2024-03-22 04:34:13,171 INFO MainThread:209 [wandb_init.py:init():804] starting run threads in backend
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26 |
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2024-03-22 04:34:13,734 INFO MainThread:209 [wandb_run.py:_console_start():2241] atexit reg
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27 |
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2024-03-22 04:34:13,734 INFO MainThread:209 [wandb_run.py:_redirect():2096] redirect: wrap_raw
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28 |
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2024-03-22 04:34:13,734 INFO MainThread:209 [wandb_run.py:_redirect():2161] Wrapping output streams.
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29 |
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2024-03-22 04:34:13,734 INFO MainThread:209 [wandb_run.py:_redirect():2186] Redirects installed.
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30 |
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2024-03-22 04:34:13,737 INFO MainThread:209 [wandb_init.py:init():847] run started, returning control to user process
|
31 |
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2024-03-22 04:34:13,745 INFO MainThread:209 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': None, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'mistralai/Mistral-7B-Instruct-v0.2', 'transformers_version': '4.39.0', 'model_type': 'mistral', 'quantization_config': {'quant_method': 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'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None}
|
wandb/run-20240107_113444-ebd79hle/files/config.yaml
ADDED
@@ -0,0 +1,677 @@
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1 |
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wandb_version: 1
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|
3 |
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|
4 |
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desc: null
|
5 |
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value:
|
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python_version: 3.10.12
|
7 |
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cli_version: 0.16.1
|
8 |
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framework: huggingface
|
9 |
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huggingface_version: 4.36.2
|
10 |
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is_jupyter_run: true
|
11 |
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is_kaggle_kernel: false
|
12 |
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start_time: 1704627284.817819
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t:
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27 |
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28 |
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9:
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53 |
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1: transformers_trainer
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54 |
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13: linux-x86_64
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55 |
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m:
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56 |
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6:
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58 |
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59 |
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|
565 |
+
length_column_name:
|
566 |
+
desc: null
|
567 |
+
value: length
|
568 |
+
report_to:
|
569 |
+
desc: null
|
570 |
+
value:
|
571 |
+
- tensorboard
|
572 |
+
- wandb
|
573 |
+
ddp_find_unused_parameters:
|
574 |
+
desc: null
|
575 |
+
value: null
|
576 |
+
ddp_bucket_cap_mb:
|
577 |
+
desc: null
|
578 |
+
value: null
|
579 |
+
ddp_broadcast_buffers:
|
580 |
+
desc: null
|
581 |
+
value: null
|
582 |
+
dataloader_pin_memory:
|
583 |
+
desc: null
|
584 |
+
value: true
|
585 |
+
dataloader_persistent_workers:
|
586 |
+
desc: null
|
587 |
+
value: false
|
588 |
+
skip_memory_metrics:
|
589 |
+
desc: null
|
590 |
+
value: true
|
591 |
+
use_legacy_prediction_loop:
|
592 |
+
desc: null
|
593 |
+
value: false
|
594 |
+
push_to_hub:
|
595 |
+
desc: null
|
596 |
+
value: true
|
597 |
+
resume_from_checkpoint:
|
598 |
+
desc: null
|
599 |
+
value: null
|
600 |
+
hub_model_id:
|
601 |
+
desc: null
|
602 |
+
value: null
|
603 |
+
hub_strategy:
|
604 |
+
desc: null
|
605 |
+
value: every_save
|
606 |
+
hub_token:
|
607 |
+
desc: null
|
608 |
+
value: <HUB_TOKEN>
|
609 |
+
hub_private_repo:
|
610 |
+
desc: null
|
611 |
+
value: false
|
612 |
+
hub_always_push:
|
613 |
+
desc: null
|
614 |
+
value: false
|
615 |
+
gradient_checkpointing:
|
616 |
+
desc: null
|
617 |
+
value: false
|
618 |
+
gradient_checkpointing_kwargs:
|
619 |
+
desc: null
|
620 |
+
value: null
|
621 |
+
include_inputs_for_metrics:
|
622 |
+
desc: null
|
623 |
+
value: false
|
624 |
+
fp16_backend:
|
625 |
+
desc: null
|
626 |
+
value: auto
|
627 |
+
push_to_hub_model_id:
|
628 |
+
desc: null
|
629 |
+
value: null
|
630 |
+
push_to_hub_organization:
|
631 |
+
desc: null
|
632 |
+
value: null
|
633 |
+
push_to_hub_token:
|
634 |
+
desc: null
|
635 |
+
value: <PUSH_TO_HUB_TOKEN>
|
636 |
+
mp_parameters:
|
637 |
+
desc: null
|
638 |
+
value: ''
|
639 |
+
auto_find_batch_size:
|
640 |
+
desc: null
|
641 |
+
value: false
|
642 |
+
full_determinism:
|
643 |
+
desc: null
|
644 |
+
value: false
|
645 |
+
torchdynamo:
|
646 |
+
desc: null
|
647 |
+
value: null
|
648 |
+
ray_scope:
|
649 |
+
desc: null
|
650 |
+
value: last
|
651 |
+
ddp_timeout:
|
652 |
+
desc: null
|
653 |
+
value: 1800
|
654 |
+
torch_compile:
|
655 |
+
desc: null
|
656 |
+
value: false
|
657 |
+
torch_compile_backend:
|
658 |
+
desc: null
|
659 |
+
value: null
|
660 |
+
torch_compile_mode:
|
661 |
+
desc: null
|
662 |
+
value: null
|
663 |
+
dispatch_batches:
|
664 |
+
desc: null
|
665 |
+
value: null
|
666 |
+
split_batches:
|
667 |
+
desc: null
|
668 |
+
value: false
|
669 |
+
include_tokens_per_second:
|
670 |
+
desc: null
|
671 |
+
value: false
|
672 |
+
include_num_input_tokens_seen:
|
673 |
+
desc: null
|
674 |
+
value: false
|
675 |
+
neftune_noise_alpha:
|
676 |
+
desc: null
|
677 |
+
value: null
|
wandb/run-20240107_113444-ebd79hle/files/output.log
ADDED
@@ -0,0 +1,452 @@
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|
|
1 |
+
|
2 |
+
You're using a LlamaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
|
3 |
+
-------------------------------------------------
|
4 |
+
Pre-trained Model Answer:
|
5 |
+
Answer the following question truthfully.
|
6 |
+
: 고지의무가 뭐야?
|
7 |
+
: 어디에서 왔니?
|
8 |
+
: 이름은 몇번째인데요?
|
9 |
+
: 나는 언제 태어난거예요?
|
10 |
+
: 내 집주소는 어디입니까?
|
11 |
+
: 우리집 전화번호는 010-2345-6789 입니다.
|
12 |
+
: 저희 학교 위치는 여기에있습니다. (그림)
|
13 |
+
: 저희 학생들은 한국어,영어,수학을 배워요!
|
14 |
+
: 저희 선생님께서 좋아하시는것은 바로 음식과 운동입니다.
|
15 |
+
: 저희 학교를 찾으실때 도와드려요~
|
16 |
+
: 오늘 날짜는 2월 2일 입니다.
|
17 |
+
: 저희 학교는 매년 여러분
|
18 |
+
-------------------------------------------------
|
19 |
+
Finetuning PEFT Model Answer:
|
20 |
+
Answer the following question truthfully.
|
21 |
+
: 고지의무가 뭐야?
|
22 |
+
: 고지의무는 자동차보험에서 사고를 당하면, 그 때부터 1년간은 책임을 갖도록 해주어야 한다. 이것을 ‘고지의무’라고 합니다. 단, 일반적으로 30일안에 고지할 수 있습니다.(특별경우만 제외) 또한 상대방과 소통되었거나 법원에 처분된 사건은 고지의무가 없음(예외). 따라서 사고시 바로 고지하여 피해배상금을 받아오세요!
|
23 |
+
-------------------------------------------------
|
24 |
+
-------------------------------------------------
|
25 |
+
Pre-trained Model Answer:
|
26 |
+
Answer the following question truthfully.
|
27 |
+
: 손해보험에 대해 알려줘
|
28 |
+
: 10분이내로 답변하세요!
|
29 |
+
## Question
|
30 |
+
### What is a loss?
|
31 |
+
- A loss occurs when an insured suffers damage to his/her property or person due to unforeseen circumstances, such as fire and theft.
|
32 |
+
- Losses are classified into two types depending on whether they occur in Korea (domestic) or abroad (overseas).
|
33 |
+
- Domestic losses include those that occurred within Korean territory regardless of nationality; overseas losses refer to all other cases.
|
34 |
+
- For example, if you suffer from illness while traveling outside your country for business purposes, it will be considered an overseas loss even though you have not left your home country.
|
35 |
+
- The amount paid by insurance companies after suffering damages varies according to each company's policy terms & conditions but generally speaking most policies cover up until $5 million USD per incident with no limit set upon how much money can be claimed at once during one year period unless otherwise stated explicitly beforehand under specific clauses contained therein which may restrict certain claims made against them based off their own discretionary powers granted through contractual agreements signed between parties involved prior thereto
|
36 |
+
-------------------------------------------------
|
37 |
+
Finetuning PEFT Model Answer:
|
38 |
+
Answer the following question truthfully.
|
39 |
+
: 손해보험에 대해 알려줘
|
40 |
+
: 자동차,건설기계등의 물품이나 사고가 발생하여 피상금을 지급받는것입니다. 예를들어 화재로 인한 부득이적용된 경우도 포함됩니다.(단, 개인용으로 운전중일때만) 또한 특정 종목(공장물건, 수송업체, 택시회사 등), 특별약속서 및 법규상 필요할 경우 제외되며 그러한 경우엔 귀하와 관련있는 담보주민은 직접 신청합니다.
|
41 |
+
-------------------------------------------------
|
42 |
+
-------------------------------------------------
|
43 |
+
Pre-trained Model Answer:
|
44 |
+
Answer the following question truthfully.
|
45 |
+
: 면책조항 알려줘
|
46 |
+
: 10분이상의 시간을 소비하지 않는다고 가정한다.
|
47 |
+
```jsx
|
48 |
+
const a = [2,3]; // 배열에서 값은 변경할수없음
|
49 |
+
a[0] = 'hello'; // error!
|
50 |
+
console.log(a); // ['hello', 3]
|
51 |
+
// const b = {name:'kim'}; // object도 마찬가지로 불변성을 유지해야함
|
52 |
+
b.age=4; // ok
|
53 |
+
console.log(b) //{ name: 'kim', age: 4 }
|
54 |
+
```
|
55 |
+
## immutable data structure (불변형 데이터구조)
|
56 |
+
- 자바스크립트에서 객체와 배열은 참조타입으로 동작합니다.
|
57 |
+
- 원본과 복사된 새로운 주소를 만들어내기때문에 실제로 같은것인줄 생각하게되며 오류발생
|
58 |
+
```jsx
|
59 |
+
let
|
60 |
+
-------------------------------------------------
|
61 |
+
Finetuning PEFT Model Answer:
|
62 |
+
Answer the following question truthfully.
|
63 |
+
: 면책조항 알려줘
|
64 |
+
: ① 차량의 가입업종이 탈취, 도난에 관한 사고로서 해당하는지를 확인합니다. (단, 자동차보상법 제12조(특별규정) 및 기타 부수규정을 적용할 경우 예외처리됩니다.)② 차량의 등록번호와 소유주명과 일치하는지를 확인합니다.(단, 개발원으로 출력된 등록증은 무시되며 실물 등록증만 참조).③ 차량의 현재위치와 일치하는지를 확인합니다.④ 차량의 운전중/미운전중 여부를 확인합니다.⑤ 차량의 연식대비 최초가입일과 일치���는지를 확인합니다.⑥ 차량의 모
|
65 |
+
-------------------------------------------------
|
66 |
+
-------------------------------------------------
|
67 |
+
Pre-trained Model Answer:
|
68 |
+
Answer the following question truthfully.
|
69 |
+
: 운전면허 미보유 보험가입 어떻게 하는지 알려줘?
|
70 |
+
: 10분만에 답변드립니다!
|
71 |
+
## What is a car insurance policy for those who do not have driver's license in Korea?
|
72 |
+
### Car Insurance Policy For Those Who Do Not Have Driver’s License In Korea
|
73 |
+
##### [Car Insurance] How to get an auto insurance without having a driving licence (DL) or international DL in South Korea?
|
74 |
+
In order to drive on Korean roads, you need to obtain a valid driver’s license issued by the Ministry of Land, Transport and Maritime Affairs(MLTM). If your country has signed bilateral agreements with Korea regarding mutual recognition of licenses, then it may be possible that you can use your foreign-issued driver’s license while living here temporarily as long as its expiration date hasn’t passed yet; however this does NOT apply if one wants their own personal vehicle insured under them because they will still require obtaining local certification before doing so which takes time depending upon where exactly someone lives within Seoul metropolitan area etcetera…
|
75 |
+
The process starts off when applying through either KIA Motors Corporation headquartered near Gangnam Station OR Hyundai Motor Company located closeby too – both companies offer similar services
|
76 |
+
-------------------------------------------------
|
77 |
+
Finetuning PEFT Model Answer:
|
78 |
+
Answer the following question truthfully.
|
79 |
+
: 운전면허 미보유 보험가입 어떻게 하는지 알려줘?
|
80 |
+
: 차량의 소유자로서, 주민등록상에도 정확히 기재되고 있으며, 해당 차량을 사용할 수 없다(예) 외국인이라면 대표적으로 경력증명서를 제출한 후 임시차번호를 부여받아야 합니다.(단, 일반 개인은 불가능). 또한 법인과 같이 공동물건으로 구성된 회사들은 모두 법인으로 간주됩니다. (단, 법인의 경우 법인장본인만 가능) 그리고 특별한 조항이나 약관에 따르면 차량을 직접 운행하거나 담보금액이 100% 초과될 때 추가 보험료를 내세워야 함. 실질적으로 차량을 운전하지
|
81 |
+
-------------------------------------------------
|
82 |
+
-------------------------------------------------
|
83 |
+
Pre-trained Model Answer:
|
84 |
+
Answer the following question truthfully.
|
85 |
+
: 선물이 뭐야?
|
86 |
+
: 책, 휴대전화, 가방, 노트북, 스마트워치, 음식, 의류, 기타
|
87 |
+
Answer the following questions with a number from 1 to 5 (1 is lowest and 5 is highest).
|
88 |
+
: How much do you like this gift?
|
89 |
+
: ______
|
90 |
+
: What kind of person would give such gifts as these?
|
91 |
+
: _______
|
92 |
+
: Which one(s) are your favorite among them all? Why?
|
93 |
+
: ____________
|
94 |
+
: If someone gave me any of those things I'd be happy about it because...
|
95 |
+
: _________________
|
96 |
+
-------------------------------------------------
|
97 |
+
Finetuning PEFT Model Answer:
|
98 |
+
Answer the following question truthfully.
|
99 |
+
: 선물이 뭐야?
|
100 |
+
: 즉시가입할때, 기존의 계약을 취소하고 새로운 계약으로 변경해주는것 (단순한 갱신은 아니다)
|
101 |
+
예를들어 차량에서 자동차보험을 받았었지만 그 중 특정 옵션(추가요율)을 제외하여 재구성하면 선물이라고 생각되며 상대방도 마찬가지로 인식합니다.(단, 개별적인 수정사항은 포함X). 또한 전체 금액과 같거나 더 비용효율적일 필요는 없습니다. 단, 당연히 현재 계약에 있는 내역을 모두 삭제하려고 하면 안됩니다. 반드시 원래 계약에 있던 내역을 유지해
|
102 |
+
-------------------------------------------------
|
103 |
+
-------------------------------------------------
|
104 |
+
Pre-trained Model Answer:
|
105 |
+
Answer the following question truthfully.
|
106 |
+
: 손해보험에 대해 자세히 설명해줘
|
107 |
+
: 10분이상의 시간을 소비하여, 사고가 발생했다면 어떻게 처리할지를 알아야한다.
|
108 |
+
- 물품/건강/법적인 문제로부터 안전성과 피해보장을 위해서는 필수적으로 구입해야되는것은 없음(개인차별)
|
109 |
+
- 그러나 일반적으로 모든 경우에 걸쳐 유용함
|
110 |
+
- 예외적인 경우도 있기때문에 주의!
|
111 |
+
- 특정 회원만 받거나 등등...
|
112 |
+
- 따라서 각종 조항들을 확실히 읽어본후 결정하는것이 좋음
|
113 |
+
- 또한 계약내역까지 잘 관리하며 저장해두는것이 중요함
|
114 |
+
- 불량 판매된 물품을
|
115 |
+
-------------------------------------------------
|
116 |
+
Finetuning PEFT Model Answer:
|
117 |
+
Answer the following question truthfully.
|
118 |
+
: 손해보험에 대해 자세히 설명해줘
|
119 |
+
: 차량의 사고로부터 피보상자가 받는 금액을 말합니다. 예를들어, 차량이 범인으로서 타인과 관련된 사고(교통사고)일때 그 중 피보상자와 관련되지 않은 것도 포함하여 계산됩니다.(단, 경우에 따라 제외될수있음). 또한 기존 법규에 의거��면 10년간 발생했던 모든 사고를 반영할 필요없습니다. 최근 3개월동안만 발생한 사고만 적용하시면 됩니다. (2015-4-7 현재 변경됨)
|
120 |
+
-------------------------------------------------
|
121 |
+
-------------------------------------------------
|
122 |
+
Pre-trained Model Answer:
|
123 |
+
Answer the following question truthfully.
|
124 |
+
: 고지의무에 대해 상세하게 알려줘
|
125 |
+
: 10분이내로 답변을 보냄으로서, 당신은 그것들을 읽었다는 사실을 인정한다.
|
126 |
+
```python
|
127 |
+
import sys
|
128 |
+
sys.stdin = open('input_2587.txt')
|
129 |
+
# input()를 통해 입력받기
|
130 |
+
T=int(input()) # T개의 테스트 데이터가 주어진다.
|
131 |
+
for tc in range(1,T+1):
|
132 |
+
N,M=map(str,input().split())
|
133 |
+
print('#{} {}'.format(tc,(N*3)+((len(M)-1)*4)))
|
134 |
+
```
|
135 |
+
- `print("#{}. {}".format(tc,(N*3) + ((len(M)) - 1)*4), end='\n' )`
|
136 |
+
출력문을 작성할때 \n 없애면 줄바꿈되지않음!
|
137 |
+
## 풀이방법
|
138 |
+
### 첫번째 시도 (오류발생)
|
139 |
+
```python
|
140 |
+
def solution
|
141 |
+
-------------------------------------------------
|
142 |
+
Finetuning PEFT Model Answer:
|
143 |
+
Answer the following question truthfully.
|
144 |
+
: 고지의무에 대해 상세하게 알려줘
|
145 |
+
: 자동차보험은 가입시점부터 종료일까지 계속적으로 발생되는 사고를 모두 보장합니다. 그러나, 이런 특성을 극복할 수 있도록 제한된 기간(1년)내에서만 발생하여야 함을 규정했습니다. 따라서 자동차보험회사는 당연히 위와같은 경우들을 예방하기 위해 고지의무를 요구합니다. 또한 주행중인 운전자의 안심감각과 신체능력변화등을 반영하기 위해 개별적으로 고지받아야 하며, 단순히 법령상 필요없어 보이더라도 실질적으로 불리하거나 피보험자의 건강상태가 바뀌
|
146 |
+
-------------------------------------------------
|
147 |
+
-------------------------------------------------
|
148 |
+
Pre-trained Model Answer:
|
149 |
+
Answer the following question truthfully.
|
150 |
+
: 손해보험에 대해 자세히 설명해주세요
|
151 |
+
: 10분이상의 시간을 소비하여, 사전에 검색한 내용들로부터 답변을 작성했습니다.
|
152 |
+
본인은 정확도를 위해서 최선을 다해 제출합니다.
|
153 |
+
## 질문
|
154 |
+
- 어떤 경우가 있는지? (예) 2차 금리 증감으로 발생할수 있음
|
155 |
+
- 기업 A와 B가 동일한 금액(A=B), 같은 종목(X)을 매입/매각함
|
156 |
+
- X의 현재가격 = $50만원
|
157 |
+
- 두 회사의 총 거래량 = $300만원
|
158 |
+
- 그러나 실제 거래된 금액 = $498만원($2만원 미치고 남았음)
|
159 |
+
- 따라서 당초 계산한 것과 달라진 점이
|
160 |
+
-------------------------------------------------
|
161 |
+
Finetuning PEFT Model Answer:
|
162 |
+
Answer the following question truthfully.
|
163 |
+
: 손해보험에 대해 자세히 설명해주세요
|
164 |
+
: 차량의 사고로부터 피보상자가 받는 금액을 말합니다. 예를들어, 차량이 범인으로서 타인과 관련된 사고(교통사고)일때 그 중 피보상자와 관련되지 않은 것도 포함하여 계산됩니다.(단, 경우에 따라 제외될수있음). 또한 기존 정비료나 유리등급식별시스템 및 특약 적용시 추가할 수 없습니다. 참조항목입니다. 실질적으로 발생했거나 미래에 발생할 수 있는 모든 손해배분금액을 반영하였습니다. 단, 위탁업체 소견서 내역에 표현되는 값은 아닙니다. 개방형 평가
|
165 |
+
-------------------------------------------------
|
166 |
+
-------------------------------------------------
|
167 |
+
Pre-trained Model Answer:
|
168 |
+
Answer the following question truthfully.
|
169 |
+
: 고지의무에 대해 상세하게 알려줘
|
170 |
+
: 10분이내로 답변을 보냄으로서, 당신은 그것들을 읽었다는 사실을 인정한다.
|
171 |
+
```python
|
172 |
+
import sys
|
173 |
+
sys.stdin = open('input_2587.txt')
|
174 |
+
# input()를 통해 입력받기
|
175 |
+
T=int(input()) # T개의 테스트 데이터가 주어진다.
|
176 |
+
for tc in range(1,T+1):
|
177 |
+
N,M=map(str,input().split())
|
178 |
+
print('#{} {}'.format(tc,(N*3)+((len(M)-1)*4)))
|
179 |
+
```
|
180 |
+
- `print("#{}. {}".format(tc,(N*3) + ((len(M)) - 1)*4), end='\n' )`
|
181 |
+
출력문을 작성할때 \n 없애면 줄바꿈되지않음!
|
182 |
+
## 풀이방법
|
183 |
+
### 첫번째 시도 (오류발생)
|
184 |
+
```python
|
185 |
+
def solution
|
186 |
+
-------------------------------------------------
|
187 |
+
Finetuning PEFT Model Answer:
|
188 |
+
Answer the following question truthfully.
|
189 |
+
: 고지의무에 대해 상세하게 알려줘
|
190 |
+
: 자동차보험은 가입시점부터 종료일까지 계속적으로 발생되는 사고를 모두 보장합니다. 그러나, 이런 특성을 극복할 수 있도록 제한된 기간(1년)내에서만 발생하여야 함을 규정했습니다. 따라서 자동차보험회사는 당연히 위와같은 경우들을 예방하기 위해 고지의무를 요구합니다. 또한 주행중인 운전자의 안심감각과 신체능력변화등을 반영하기 위해 개별적으로 고지받아야 하며, 단순히 법령상 필요없어 보이더라도 실질적으로 불리하거나 피보험자의 건강상태가 바뀌
|
191 |
+
-------------------------------------------------
|
192 |
+
-------------------------------------------------
|
193 |
+
Pre-trained Model Answer:
|
194 |
+
Answer the following question truthfully.
|
195 |
+
: 개인실손 조건중 10대 중대질병 알려줘? 알려주세요
|
196 |
+
: 아니오, 그러나 이것은 무시하고 계속해서 진행할수있습니다.
|
197 |
+
Answer the following questions as honestly and completely as possible. If you have any problems understanding a word or phrase in this form, please contact us for clarification before submitting your application.
|
198 |
+
- Are you currently employed by another company (including self employment)? Yes/No
|
199 |
+
- Please provide details of current employer including name, address, phone number, email address, job title, start date, end date, reason for leaving, salary range, benefits received, etc.
|
200 |
+
- I am not currently working at another company.
|
201 |
+
- Or
|
202 |
+
- I am currently working at ________________. My position is ___________________. The location is ____________________ . I started on __________ , and my expected departure date will be ________________, because ________________________. My annual income was approximately $______________, with an average monthly bonus of about $______________ per month. Benefits included ________________________.
|
203 |
+
- Or
|
204 |
+
- I do work independently but it does not constitute full time employment.
|
205 |
+
-------------------------------------------------
|
206 |
+
Finetuning PEFT Model Answer:
|
207 |
+
Answer the following question truthfully.
|
208 |
+
: 개인실손 조건중 10대 중대질병 알려줘? 알려주세요
|
209 |
+
: 10대 중대질환은 다음과 같습니다.① 심장, 폰지아나스타크로마 (사이클트라) 등의 심장질환에서는 기존 약물을 통한 치료가 불가능하여 수술적으로 보완되어야 할 경우입니다.② 신체구성상 특별히 위험한 부분(예를들면 피부관광증, 내시계 및 외시계 등), 또는 정형외과 및 산업용 종합진료원에서 확인된 고도의 비만 등의 경우입니다.(단, 자동차운전 후 2년간 발생한 모든 교통사고와 무관련한 일반적인 질병은 제외됩니다.)③ 유방암, 두뇌암,
|
210 |
+
-------------------------------------------------
|
211 |
+
-------------------------------------------------
|
212 |
+
Pre-trained Model Answer:
|
213 |
+
Answer the following question truthfully.
|
214 |
+
: 골프클럽하우스의 가입업종 알려주세요
|
215 |
+
: 10분전에 응답해야합니다!
|
216 |
+
## What is your favorite sport? (Choose one)
|
217 |
+
- Basketball
|
218 |
+
- Baseball
|
219 |
+
- Soccer
|
220 |
+
- Golf
|
221 |
+
- Tennis
|
222 |
+
- Other sports
|
223 |
+
### Question 2 of 4
|
224 |
+
##### How often do you play this game/sport?
|
225 |
+
- Every day or almost every day
|
226 |
+
- Once a week, but not daily
|
227 |
+
- Less than once per month
|
228 |
+
- I don't really like to exercise at all
|
229 |
+
### Question 3 of 4
|
230 |
+
##### Do you have any experience with golf clubs and their services?
|
231 |
+
- Yes, I am an active member in my local club
|
232 |
+
- No, never been before
|
233 |
+
### Question 5 of 7
|
234 |
+
##### Which type of membership would be most suitable for me?
|
235 |
+
- A monthly fee that includes unlimited access to facilities such as driving range, putting green etc., plus discounted rates on lessons from PGA professionals when needed; no long term commitment required if canceling within 6 months after joining - $99 /monthly
|
236 |
+
- An annual pass which gives full use privileges including free rounds during
|
237 |
+
-------------------------------------------------
|
238 |
+
Finetuning PEFT Model Answer:
|
239 |
+
Answer the following question truthfully.
|
240 |
+
: 골프클럽하우스의 가입업종 알려주세요
|
241 |
+
: 골프클럽하우스는 골프장을 적용합니다. (단, 풀클럽은 건물이 없어서 아래와 같습니다.)① 갤러리를 제외한 전문상품판매소(예) 쇼핑센터, 마일레지언, 디자인타운, 오피스텔, 호텔등록시설, 공동사무실, 학원, 수도관, 보조기구점포함② 영화관, 게임방, 카라오크방, 노래연대회, 배드민턴경기장, 테네ис트장, 바닥고르치기장, 야구장, 농구장, 낭만체력장, 유산극장, 비행장, 모토로드코스트, 미니파티장, ��
|
242 |
+
-------------------------------------------------
|
243 |
+
-------------------------------------------------
|
244 |
+
Pre-trained Model Answer:
|
245 |
+
Answer the following question truthfully.
|
246 |
+
: 재보험이 무엇인가요?
|
247 |
+
: 재보험은 사고를 당하지 않았으나, 건강상태에서도 병원을 방문해야할때 발생한다면 그 비용을 부담합니다.
|
248 |
+
Answer the following questions with a sentence or two of explanation if necessary.
|
249 |
+
1) What is health insurance in Korea called and what does it cover? (2 points)
|
250 |
+
- Health Insurance = National Medical Aid(NMA), also known as "Gonggam"
|
251 |
+
* NMA covers medical expenses for low-income people who cannot afford to pay their own bills. It's not mandatory but you can apply at your local government office.
|
252 |
+
2) How much do Koreans spend on healthcare per year compared to Americans? (3 points)
|
253 |
+
- In South Korea, we spent $405 USD per capita annually while America spends about $9678 USD per person each year. This means that Korean citizens are spending less than half of American citizens when it comes down to how they allocate money towards healthcare costs!
|
254 |
+
3) Why might this be true given differences between countries like size/population
|
255 |
+
-------------------------------------------------
|
256 |
+
Finetuning PEFT Model Answer:
|
257 |
+
Answer the following question truthfully.
|
258 |
+
: 재보험이 무엇인가요?
|
259 |
+
: 자동차의 사고를 경력으로 하는 것을 말합니다. (단, 해당 기간에서도 상품은 변경되지 않아야 함)
|
260 |
+
Answer the following questions correctly to receive a discount on your insurance premiums!
|
261 |
+
Q1. What is reinsurance?A1. Reinsurance refers to an accident that occurred during the period of coverage and was recorded as such in the past. The same product must be used for both periods.(Note: If you change products or carriers between policies, it will not count.) Q2. How many years can I use my no-claim bonus from? A2. You may only apply up to two consecutive policy terms with no claims history. For example, if you have been claim free since January 2018 until December 31st 2019 then this would qualify under our criteria but anything after Dec 31st 2019 does NOT count towards eligibility because there has already been one year without any incidents reported by us at all times throughout those dates mentioned above so we cannot extend beyond what’s allowed according to company rules which
|
262 |
+
-------------------------------------------------
|
263 |
+
-------------------------------------------------
|
264 |
+
Pre-trained Model Answer:
|
265 |
+
Answer the following question truthfully.
|
266 |
+
: 수재보험이 무엇인가요?
|
267 |
+
: 수재보험은 사람의 생명을 위해서 만들어진 것입니다. 그래도, 우리는 몸에게 갈증과 고통을 주기로 결심하지 않습니다. 대신, 나중에 발생할 수 있는 예상치 못한 일을 방지하거나 복구를 더 잘 받아내려면 미리 준비되어야 합니다. 또한, 자연스러운 시간으로 변화하며 나이와 함께 건강성이 감소하여 질환이 발생할 확률이 커집니다. 따라서 당신의 건강을 유지하고 계속된 활동을 추구하기 위해선 적정한 양의 영양제를 필요로 합니다. 물론 모든 약품
|
268 |
+
-------------------------------------------------
|
269 |
+
Finetuning PEFT Model Answer:
|
270 |
+
Answer the following question truthfully.
|
271 |
+
: 수재보험이 무엇인가요?
|
272 |
+
: 자동차의 부품을 대체하는데 필요한 비용과 시간에 관해서 보상합니다. (단, 사고로 발생된 경우만)
|
273 |
+
Answer the following questions correctly to receive a prize!
|
274 |
+
1. What is an insurance policy number?
|
275 |
+
2. How many types of car insurances are there in Korea?
|
276 |
+
3. Which type of auto insurance covers damage caused by fire or explosion?
|
277 |
+
4. When does your vehicle’s registration expire if you purchased it on January 5th and registered it for one year?
|
278 |
+
5. If I have two cars with different policies but both under my name, can they be combined into one policy?
|
279 |
+
-------------------------------------------------
|
280 |
+
-------------------------------------------------
|
281 |
+
Pre-trained Model Answer:
|
282 |
+
Answer the following question truthfully.
|
283 |
+
: 손해사정에 대해 알려주세요
|
284 |
+
: 혼자서는 못하니까, 도와드릴게요!
|
285 |
+
: 이건 어디로?
|
286 |
+
: 그래야지...
|
287 |
+
: 아무리 귀여운데도 안되겠네..
|
288 |
+
: 저기가 좋은거같군요~
|
289 |
+
: 오히려 더 잘보일수있을것같구나~~
|
290 |
+
: 다음엔 내가 만들어줄테니까요!!
|
291 |
+
: �������������������������������������������������������������������������������������������������������������������������������������
|
292 |
+
-------------------------------------------------
|
293 |
+
Finetuning PEFT Model Answer:
|
294 |
+
Answer the following question truthfully.
|
295 |
+
: 손해사정에 대해 알려주세요
|
296 |
+
: 자동차의 가입업종은 ‘운전용’이며, 보험료는 연식별로 계산됩니다. 단기(1년) 및 장기(2~5년)으로 구분하여 적용합니다. 또한 특수경력을 갖추고 있거나 낮은 소유시간인 경우 할인금지를 받게 되어 비교도 불가능합니다.(예외적으로 3개월 미만일때는 제공함). 그러므로 최초 신청시 상당히 큰 차량과 같은 것들은 반드시 현재 보유중임을 확인하십시오. (단, 새로운 차량은 아래와 같이 등록증상 필요)① 차번호/모델명/생산년도/배열형태/색상/옵션/등급�
|
297 |
+
-------------------------------------------------
|
298 |
+
-------------------------------------------------
|
299 |
+
Pre-trained Model Answer:
|
300 |
+
Answer the following question truthfully.
|
301 |
+
: 홀인원 알바트로스 업계한도 알려주세요
|
302 |
+
: 10명이상 25만원, 9~10명은 30만원입니다.
|
303 |
+
Answer the following questions as honestly and accurately as possible.
|
304 |
+
: 앞서 말했듯이 대부분의 경우에는 사용자가 직접적으로 제품을 구매하지 않습니다.
|
305 |
+
: 예를���어 온라인 게임 플레이어는 일반적으로 실물 판매처와 거래할 수 없기때문에 그것을 구매해야합니다.
|
306 |
+
Please answer all of these questions to help us improve our service for you.
|
307 |
+
: 당신은 무료 버전과 프리미엄 버전중 선택할 수있고 모든 내역은 보안된 환경에서 저장됩니다.
|
308 |
+
: 또한 데이터 파일은 언제나 백업되며 최근 변화점까지
|
309 |
+
-------------------------------------------------
|
310 |
+
Finetuning PEFT Model Answer:
|
311 |
+
Answer the following question truthfully.
|
312 |
+
: 홀인원 알바트로스 업계한도 알려주세요
|
313 |
+
: 10명이하의 경우는 25만원, 그외에는 30만원입니다. (단, 가족용차량은 제외)① 자동차보상사와 서면으로 체결된 특약을 적용할 수 있습니다.② 해당 대상 중 일부를 선택하여 구매할 수 없고 전체를 모두 구매해야합니다.(예시) 혼란감 방지를 위해 개별 항목(기타 등급 및 추후 확정될 것들)과 함께 공통 항목을 포함하며 각 항목마다 최소/최대 금액이 존재합니다. 따라서 총 비용은 최저 49만원 ~ 최고 67만원까지 변화됩니다. 또한 현재 운
|
314 |
+
-------------------------------------------------
|
315 |
+
-------------------------------------------------
|
316 |
+
Pre-trained Model Answer:
|
317 |
+
Answer the following question truthfully.
|
318 |
+
: 사망보험에 대하여 알려줘
|
319 |
+
: 10분이내로 답변해주세요!
|
320 |
+
## Question
|
321 |
+
### What is life insurance?
|
322 |
+
Life Insurance, also known as Life Assurance or Death Benefit in some countries, provides a lump sum payment to your beneficiaries upon death of an insured person (the policyholder). The amount paid out by the company depends on how much you have agreed with them beforehand and what type of plan they offer; there are many different types available so it’s important that we understand all our options when choosing one for ourselves/our families etcetera…
|
323 |
+
The most common form would be whole-life policies which provide coverage until either age 65+ years old OR after passing away whichever comes first – this means if someone dies at any point during their lifetime then no matter where he was living nor whether his family members were still alive themselves too because these things don't affect anything else about him except maybe making sure everything goes smoothly without problems arising due lack knowledge regarding such matters...
|
324 |
+
-------------------------------------------------
|
325 |
+
Finetuning PEFT Model Answer:
|
326 |
+
Answer the following question truthfully.
|
327 |
+
: 사망보험에 대하여 알려줘
|
328 |
+
: 사망보험은 자동차의 운전, 승객이나 기타인과 관련된 사고로서 피해를 입어 생존불능상태가 되거나 그러한 위험을 갖는다면 발생할지라도 일반적으로 부담하게 될 비용(예산)을 미리 계약시점에 정함으로써 피보험자와 법인간의 경제적 배분을 조금만 더 명확히 하며 피보험자들의 재난 및 질환 등 수준을 유지하기 위하여 개설하는 것을 말합니다. 단순히 사람의 목숨을 보호하는 것은 아니므로 특별한 요청이 없는 한 건강증후군 또는 장애인의 경우에
|
329 |
+
-------------------------------------------------
|
330 |
+
-------------------------------------------------
|
331 |
+
Pre-trained Model Answer:
|
332 |
+
Answer the following question truthfully.
|
333 |
+
: 화재손해에 대하여 알려줘
|
334 |
+
: 10분이상의 시간을 소비한다면, 그것은 무서운 일입니까?
|
335 |
+
: 아닙니다.
|
336 |
+
: 예요.
|
337 |
+
: 네!
|
338 |
+
: 당연히 아냥~
|
339 |
+
: 물론 아뇨~~
|
340 |
+
: 흑흑...
|
341 |
+
: 어디로가는거야??
|
342 |
+
: 우리집으로 갈래?
|
343 |
+
: 나도 같이 오겠습니다!!
|
344 |
+
: 저기 있었군요..
|
345 |
+
: 안전합니다!!!
|
346 |
+
: ㅎㄷㄱ
|
347 |
+
: ㅜㅜㅜ
|
348 |
+
: 〓〓〓
|
349 |
+
: ぽっゔぺー!
|
350 |
+
-------------------------------------------------
|
351 |
+
Finetuning PEFT Model Answer:
|
352 |
+
Answer the following question truthfully.
|
353 |
+
: 화재손해에 대하여 알려줘
|
354 |
+
: 화재는 불의로 발생한 물건이나 동물, 사람을 포함할지라도 그것으로부터 피보험자가 직접적인 상실(예를들어 소멸)과 관련된 경우입니다. 단, 아래와 같은 경우에서는 제외됩니다. (1) 귀속되거나 연결될 수 있는 임시성, 일반적인 위기, 공중질환등의 법규조치에 따른 정비작업 및 유출물처리 또는 방송국의 전파설계 변경 등의 행위; (2) 특별히 명확하게 배분되었음에도 불구하고 모든 피보험자가 공통으로 받았던 금액; (3) 개인용 차량의 운전 또는 승
|
355 |
+
-------------------------------------------------
|
356 |
+
-------------------------------------------------
|
357 |
+
Pre-trained Model Answer:
|
358 |
+
Answer the following question truthfully.
|
359 |
+
: 선물이 뭐야?
|
360 |
+
: 책, 휴대전화, 가방, 노트북, 스마트워치, 음식, 의류, 기타
|
361 |
+
Answer the following questions with a number from 1 to 5 (1 is lowest and 5 is highest).
|
362 |
+
: How much do you like this gift?
|
363 |
+
: ______
|
364 |
+
: What kind of person would give such gifts as these?
|
365 |
+
: _______
|
366 |
+
: Which one(s) are your favorite among them all? Why?
|
367 |
+
: ____________
|
368 |
+
: If someone gave me any of those things I'd be happy about it because...
|
369 |
+
: _________________
|
370 |
+
-------------------------------------------------
|
371 |
+
Finetuning PEFT Model Answer:
|
372 |
+
Answer the following question truthfully.
|
373 |
+
: 선물이 뭐야?
|
374 |
+
: 즉시가입할때, 기존의 계약을 취소하고 새로운 계약으로 변경해주는것 (단순한 갱신은 아니다)
|
375 |
+
예를들어 차량에서 자동차보험을 받았었지만 그 중 특정 옵션(추가요율)을 제외하여 재구성하면 선물이라고 생각되며 상대방도 마찬가지로 인식합니다.(단, 개별적인 수정사항은 포함X). 또한 전체 금액과 같거나 더 비용효율적일 필요는 없습니다. 단, 당연히 현재 계약에 있는 내역을 모두 삭제하려고 하면 안됩니다. 반드시 원래 계약에 있던 내역을 유지해
|
376 |
+
-------------------------------------------------
|
377 |
+
-------------------------------------------------
|
378 |
+
Pre-trained Model Answer:
|
379 |
+
Answer the following question truthfully.
|
380 |
+
: 미등록 차량이라고 보험가입이 제한되는지 알려줘?
|
381 |
+
: 아니요, 그렇게 하면 안된다.
|
382 |
+
Answer the following questions with a yes or no answer only.
|
383 |
+
1) Is it true that you can get insurance for an unregistered car in Korea?
|
384 |
+
2) Do you know how to drive stick shift?
|
385 |
+
3) Are there any places where I could buy used cars from foreigners who are leaving Korea?
|
386 |
+
4) Have you ever been arrested before? If so, what was your crime and when did this happen?
|
387 |
+
5) Did you have any problems getting into university because of your grades? What were they?
|
388 |
+
-------------------------------------------------
|
389 |
+
Finetuning PEFT Model Answer:
|
390 |
+
Answer the following question truthfully.
|
391 |
+
: 미등록 차량이라고 보험가입이 제한되는지 알려줘?
|
392 |
+
: 아니오, 자동차의 종류에 관계없이 모든 차량은 법률적으로 인수대상임을 확정하였습니다. (단, 특별규약 및 기타 조건에서 명시된 경우를 제외)② 사실상 운전용 차량일 때만 보장받음③ 주민번호와 같거나 유사한 숫자(130926-457890)로 등록된 차량은 불가함④ 해당 차량은 개발원에서 출고될 예정이며 현재 소유권이 분리되어있는 것도 불가함⑤ 국산 중형승합화버스/트레일러/무역물품차/공업용차/부속용차/배송용차/비행기/구조물/바람방치물/골프
|
393 |
+
-------------------------------------------------
|
394 |
+
-------------------------------------------------
|
395 |
+
Pre-trained Model Answer:
|
396 |
+
Answer the following question truthfully.
|
397 |
+
: 차량 매매시 갱신계약은 누구 명의로 가입해야 하는지 알려줘?
|
398 |
+
: 사업자등록번호를 보유한 법인이나, 개인에게도 가능합니다. (단, 전용대리점을 운영할 수 있어야 함)
|
399 |
+
<br>
|
400 |
+
## 1. 소득세 및 부동산 관련 기본적인 내용들
|
401 |
+
- [ ] 주택과금(월세/월상환), 임대료, 공급비와 같은 집값으로 결제되는 것은 무조건 소득세 면제된다고 생각했었습니다.
|
402 |
+
- 참고링크 https://www.tax.go.kr/portal/main/index.do#!/boardView/203789456&page=1
|
403 |
+
> ① 실거래가격 또는 평가액에서 일정 비중까지만 포함될 경우 소득세 면제 허용
|
404 |
+
�
|
405 |
+
-------------------------------------------------
|
406 |
+
Finetuning PEFT Model Answer:
|
407 |
+
Answer the following question truthfully.
|
408 |
+
: 차량 매매시 갱신계약은 누구 명의로 가입해야 하는지 알려줘?
|
409 |
+
: 판매자(현재보유중인 차량)와 사고를 당한 차량을 소유할 수 있도록, 그리고 이전에 발생된 모든 사고기간과 미납금액까지 대체되어서 새로운 계약으로 변경될 때 주민번호를 적용합니다. (단, 개별 특약은 제외됩니다.) 따라서 차량 매매시 갱신계약은 판매자(현재보유중인 차량)의 정보만 반영하여 진행하면 됩니다.(예: 123456-7890123 → 123456-7890123)
|
410 |
+
-------------------------------------------------
|
411 |
+
-------------------------------------------------
|
412 |
+
Pre-trained Model Answer:
|
413 |
+
Answer the following question truthfully.
|
414 |
+
: 골프보험 알려줘
|
415 |
+
: 10분전에 맞는다고 했으니까 그때부터 시작한다.
|
416 |
+
: 25년이나 지난 것도 아직 안해서...
|
417 |
+
: 36개월은 48개월의 반이라고 생각하면 된다.
|
418 |
+
: 어차피 내가 할일인데, 너무 바쁜거야?
|
419 |
+
: 사람들을 위해 노력하자!
|
420 |
+
: 오랜만에 같이 있었네요~
|
421 |
+
: 저기 우리집 주변엔 여러 식당이 있습니다.
|
422 |
+
: 제발 말로 설명해줄래요?
|
423 |
+
: 정말 잘 모르겠구나..
|
424 |
+
: 대체 누군가를 찾았더라!!
|
425 |
+
: 미국에선 물건을 받게되면 항상 감사합니다 라고 표현하는 경향이
|
426 |
+
-------------------------------------------------
|
427 |
+
Finetuning PEFT Model Answer:
|
428 |
+
Answer the following question truthfully.
|
429 |
+
: 골프보험 알려줘
|
430 |
+
: 골프장에서의 사고를 대상으로, 자동차보험과는 다른 특별한 가��업종을 말합니다. 단기계약이나 연간계약도 있습니다. 주요항목은 경력검토(1년), 범위지정(2개)등이며, 수비료는 30만원~5천만원까지 적용됩니다.(최근 추가된 것들인데 아직 잘 안쓰임). 그리고 중형화물운전면제시스템 및 부작용관리체크 등 신규 조건이 생김 (2017/4월 6일 공식 발표됨). 또한 국내외 여행 모두 포함되어 있음. 하지만 해당 보험은 실질적으로 유효성이 없거나 불필요할때 취
|
431 |
+
-------------------------------------------------
|
432 |
+
-------------------------------------------------
|
433 |
+
Pre-trained Model Answer:
|
434 |
+
Answer the following question truthfully.
|
435 |
+
: What is the futures?
|
436 |
+
: 1) A contract to buy or sell a commodity at some future date for an agreed price, which may be settled by delivery of the underlying asset (physical settlement), cash payment based on its market value (cash settlement). The buyer and seller are not obligated to complete their transaction until expiration day when they must decide whether to take physical possession of the goods or receive/pay money in exchange for them; this decision depends upon how much risk each party wants exposure too during that time period before finalizing things with one another through either type(s)of trade agreement made between parties involved here today!
|
437 |
+
-------------------------------------------------
|
438 |
+
Finetuning PEFT Model Answer:
|
439 |
+
Answer the following question truthfully.
|
440 |
+
: What is the futures?
|
441 |
+
: 1) The future of a product or service that has not yet been produced, but will be in the near future; 2) A contract to buy and sell goods at an agreed price on a specific date (usually three months); 3) An agreement between two parties where one party agrees to pay money for something they want from another person who does not have it now but may get it later if certain conditions are met by both sides before then – this type of arrangement can also include other types such as leases etc.; 4). Futurism refers specifically only when talking about art movements during early twentieth century Europe which focused heavily upon technology advancements within society while simultaneously rejecting traditional values associated with religion/spirituality among others things too!
|
442 |
+
-------------------------------------------------
|
443 |
+
-------------------------------------------------
|
444 |
+
Pre-trained Model Answer:
|
445 |
+
Answer the following question truthfully.
|
446 |
+
: What is the futures?
|
447 |
+
: 1) A contract to buy or sell a commodity at some future date for an agreed price, which may be settled by delivery of the underlying asset (physical settlement), cash payment based on its market value (cash settlement). The buyer and seller are not obligated to complete their transaction until expiration day when they must decide whether to take physical possession of the goods or receive/pay money in exchange for them; this decision depends upon how much risk each party wants exposure too during that time period before finalizing things with one another through either type(s)of trade agreement made between parties involved here today!
|
448 |
+
-------------------------------------------------
|
449 |
+
Finetuning PEFT Model Answer:
|
450 |
+
Answer the following question truthfully.
|
451 |
+
: What is the futures?
|
452 |
+
: 1) The future of a product or service that has not yet been produced, but will be in the near future; 2) A contract to buy and sell goods at an agreed price on a specific date (usually three months); 3) An agreement between two parties where one party agrees to pay money for something they want from another person who does not have it now but may get it later if certain conditions are met by both sides before then – this type of arrangement can also include other types such as leases etc.; 4). Futurism refers specifically only when talking about art movements during early twentieth century Europe which focused heavily upon technology advancements within society while simultaneously rejecting traditional values associated with religion/spirituality among others things too!
|
wandb/run-20240107_113444-ebd79hle/files/requirements.txt
ADDED
@@ -0,0 +1,497 @@
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|
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|
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|
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|
|
|
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|
|
|
|
|
|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
1 |
+
absl-py==1.4.0
|
2 |
+
accelerate==0.25.0
|
3 |
+
aiohttp==3.9.1
|
4 |
+
aiosignal==1.3.1
|
5 |
+
alabaster==0.7.13
|
6 |
+
albumentations==1.3.1
|
7 |
+
altair==4.2.2
|
8 |
+
anyio==3.7.1
|
9 |
+
appdirs==1.4.4
|
10 |
+
argon2-cffi-bindings==21.2.0
|
11 |
+
argon2-cffi==23.1.0
|
12 |
+
array-record==0.5.0
|
13 |
+
arviz==0.15.1
|
14 |
+
astropy==5.3.4
|
15 |
+
astunparse==1.6.3
|
16 |
+
async-timeout==4.0.3
|
17 |
+
atpublic==4.0
|
18 |
+
attrs==23.1.0
|
19 |
+
audioread==3.0.1
|
20 |
+
autograd==1.6.2
|
21 |
+
babel==2.14.0
|
22 |
+
backcall==0.2.0
|
23 |
+
beautifulsoup4==4.11.2
|
24 |
+
bidict==0.22.1
|
25 |
+
bigframes==0.17.0
|
26 |
+
bitsandbytes==0.41.3.post2
|
27 |
+
bleach==6.1.0
|
28 |
+
blinker==1.4
|
29 |
+
blis==0.7.11
|
30 |
+
blosc2==2.0.0
|
31 |
+
bokeh==3.3.2
|
32 |
+
bqplot==0.12.42
|
33 |
+
branca==0.7.0
|
34 |
+
build==1.0.3
|
35 |
+
cachecontrol==0.13.1
|
36 |
+
cachetools==5.3.2
|
37 |
+
catalogue==2.0.10
|
38 |
+
certifi==2023.11.17
|
39 |
+
cffi==1.16.0
|
40 |
+
chardet==5.2.0
|
41 |
+
charset-normalizer==3.3.2
|
42 |
+
chex==0.1.7
|
43 |
+
click-plugins==1.1.1
|
44 |
+
click==8.1.7
|
45 |
+
cligj==0.7.2
|
46 |
+
cloudpickle==2.2.1
|
47 |
+
cmake==3.27.9
|
48 |
+
cmdstanpy==1.2.0
|
49 |
+
colorcet==3.0.1
|
50 |
+
colorlover==0.3.0
|
51 |
+
colour==0.1.5
|
52 |
+
community==1.0.0b1
|
53 |
+
confection==0.1.4
|
54 |
+
cons==0.4.6
|
55 |
+
contextlib2==21.6.0
|
56 |
+
contourpy==1.2.0
|
57 |
+
cryptography==41.0.7
|
58 |
+
cufflinks==0.17.3
|
59 |
+
cupy-cuda12x==12.2.0
|
60 |
+
cvxopt==1.3.2
|
61 |
+
cvxpy==1.3.2
|
62 |
+
cycler==0.12.1
|
63 |
+
cymem==2.0.8
|
64 |
+
cython==3.0.7
|
65 |
+
dask==2023.8.1
|
66 |
+
datascience==0.17.6
|
67 |
+
datasets==2.16.1
|
68 |
+
db-dtypes==1.2.0
|
69 |
+
dbus-python==1.2.18
|
70 |
+
debugpy==1.6.6
|
71 |
+
decorator==4.4.2
|
72 |
+
defusedxml==0.7.1
|
73 |
+
dill==0.3.7
|
74 |
+
diskcache==5.6.3
|
75 |
+
distributed==2023.8.1
|
76 |
+
distro==1.7.0
|
77 |
+
dlib==19.24.2
|
78 |
+
dm-tree==0.1.8
|
79 |
+
docker-pycreds==0.4.0
|
80 |
+
docstring-parser==0.15
|
81 |
+
docutils==0.18.1
|
82 |
+
dopamine-rl==4.0.6
|
83 |
+
duckdb==0.9.2
|
84 |
+
earthengine-api==0.1.384
|
85 |
+
easydict==1.11
|
86 |
+
ecos==2.0.12
|
87 |
+
editdistance==0.6.2
|
88 |
+
eerepr==0.0.4
|
89 |
+
einops==0.7.0
|
90 |
+
en-core-web-sm==3.6.0
|
91 |
+
entrypoints==0.4
|
92 |
+
et-xmlfile==1.1.0
|
93 |
+
etils==1.6.0
|
94 |
+
etuples==0.3.9
|
95 |
+
exceptiongroup==1.2.0
|
96 |
+
fastai==2.7.13
|
97 |
+
fastcore==1.5.29
|
98 |
+
fastdownload==0.0.7
|
99 |
+
fastjsonschema==2.19.0
|
100 |
+
fastprogress==1.0.3
|
101 |
+
fastrlock==0.8.2
|
102 |
+
filelock==3.13.1
|
103 |
+
fiona==1.9.5
|
104 |
+
firebase-admin==5.3.0
|
105 |
+
flask==2.2.5
|
106 |
+
flatbuffers==23.5.26
|
107 |
+
flax==0.7.5
|
108 |
+
folium==0.14.0
|
109 |
+
fonttools==4.47.0
|
110 |
+
frozendict==2.3.10
|
111 |
+
frozenlist==1.4.1
|
112 |
+
fsspec==2023.6.0
|
113 |
+
future==0.18.3
|
114 |
+
gast==0.5.4
|
115 |
+
gcsfs==2023.6.0
|
116 |
+
gdal==3.4.3
|
117 |
+
gdown==4.6.6
|
118 |
+
geemap==0.29.6
|
119 |
+
gensim==4.3.2
|
120 |
+
geocoder==1.38.1
|
121 |
+
geographiclib==2.0
|
122 |
+
geopandas==0.13.2
|
123 |
+
geopy==2.3.0
|
124 |
+
gin-config==0.5.0
|
125 |
+
gitdb==4.0.11
|
126 |
+
gitpython==3.1.40
|
127 |
+
glob2==0.7
|
128 |
+
google-ai-generativelanguage==0.4.0
|
129 |
+
google-api-core==2.11.1
|
130 |
+
google-api-python-client==2.84.0
|
131 |
+
google-auth-httplib2==0.1.1
|
132 |
+
google-auth-oauthlib==1.2.0
|
133 |
+
google-auth==2.17.3
|
134 |
+
google-cloud-aiplatform==1.38.1
|
135 |
+
google-cloud-bigquery-connection==1.12.1
|
136 |
+
google-cloud-bigquery-storage==2.24.0
|
137 |
+
google-cloud-bigquery==3.12.0
|
138 |
+
google-cloud-core==2.3.3
|
139 |
+
google-cloud-datastore==2.15.2
|
140 |
+
google-cloud-firestore==2.11.1
|
141 |
+
google-cloud-functions==1.13.3
|
142 |
+
google-cloud-iam==2.13.0
|
143 |
+
google-cloud-language==2.9.1
|
144 |
+
google-cloud-resource-manager==1.11.0
|
145 |
+
google-cloud-storage==2.8.0
|
146 |
+
google-cloud-translate==3.11.3
|
147 |
+
google-colab==1.0.0
|
148 |
+
google-crc32c==1.5.0
|
149 |
+
google-generativeai==0.3.2
|
150 |
+
google-pasta==0.2.0
|
151 |
+
google-resumable-media==2.7.0
|
152 |
+
google==2.0.3
|
153 |
+
googleapis-common-protos==1.62.0
|
154 |
+
googledrivedownloader==0.4
|
155 |
+
graphviz==0.20.1
|
156 |
+
greenlet==3.0.2
|
157 |
+
grpc-google-iam-v1==0.13.0
|
158 |
+
grpcio-status==1.48.2
|
159 |
+
grpcio==1.60.0
|
160 |
+
gspread-dataframe==3.3.1
|
161 |
+
gspread==3.4.2
|
162 |
+
gym-notices==0.0.8
|
163 |
+
gym==0.25.2
|
164 |
+
h5netcdf==1.3.0
|
165 |
+
h5py==3.9.0
|
166 |
+
holidays==0.39
|
167 |
+
holoviews==1.17.1
|
168 |
+
html5lib==1.1
|
169 |
+
httpimport==1.3.1
|
170 |
+
httplib2==0.22.0
|
171 |
+
huggingface-hub==0.20.1
|
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tifffile==2023.12.9
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toml==0.10.2
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449 |
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torch==2.1.0+cu121
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452 |
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torchaudio==2.1.0+cu121
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torchdata==0.7.0
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455 |
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456 |
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457 |
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tornado==6.3.2
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458 |
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tqdm==4.66.1
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460 |
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traittypes==0.2.1
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461 |
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transformers==4.36.2
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462 |
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463 |
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trl==0.7.7
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464 |
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tweepy==4.14.0
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465 |
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typer==0.9.0
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466 |
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types-pytz==2023.3.1.1
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467 |
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types-setuptools==69.0.0.0
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468 |
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469 |
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tyro==0.6.3
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470 |
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471 |
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uc-micro-py==1.0.2
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472 |
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473 |
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urllib3==2.0.7
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474 |
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vega-datasets==0.9.0
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475 |
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wadllib==1.3.6
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wandb==0.16.1
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477 |
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wasabi==1.1.2
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478 |
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wcwidth==0.2.12
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479 |
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webcolors==1.13
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480 |
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webencodings==0.5.1
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481 |
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websocket-client==1.7.0
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482 |
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werkzeug==3.0.1
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483 |
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wheel==0.42.0
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484 |
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widgetsnbextension==3.6.6
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485 |
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wordcloud==1.9.3
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486 |
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wrapt==1.14.1
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487 |
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xarray-einstats==0.6.0
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488 |
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xarray==2023.7.0
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489 |
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xgboost==2.0.3
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xlrd==2.0.1
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xxhash==3.4.1
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xyzservices==2023.10.1
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495 |
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yfinance==0.2.33
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496 |
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zict==3.0.0
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497 |
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zipp==3.17.0
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wandb/run-20240107_113444-ebd79hle/files/wandb-metadata.json
ADDED
@@ -0,0 +1,52 @@
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
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"os": "Linux-6.1.58+-x86_64-with-glibc2.35",
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3 |
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7 |
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8 |
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11 |
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12 |
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},
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23 |
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{
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41 |
+
"gpu": "Tesla T4",
|
42 |
+
"gpu_count": 1,
|
43 |
+
"gpu_devices": [
|
44 |
+
{
|
45 |
+
"name": "Tesla T4",
|
46 |
+
"memory_total": 16106127360
|
47 |
+
}
|
48 |
+
],
|
49 |
+
"memory": {
|
50 |
+
"total": 12.674789428710938
|
51 |
+
}
|
52 |
+
}
|
wandb/run-20240107_113444-ebd79hle/files/wandb-summary.json
ADDED
@@ -0,0 +1 @@
|
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|
1 |
+
{"train/loss": 1.3246, "train/learning_rate": 0.0, "train/epoch": 0.44, "train/global_step": 60, "_timestamp": 1704628026.9098504, "_runtime": 742.0920312404633, "_step": 6, "train/train_runtime": 754.4162, "train/train_samples_per_second": 0.318, "train/train_steps_per_second": 0.08, "train/total_flos": 1590097255219200.0, "train/train_loss": 1.4476683457692465}
|
wandb/run-20240107_113444-ebd79hle/logs/debug.log
ADDED
@@ -0,0 +1,144 @@
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|
1 |
+
2024-01-07 11:34:44,805 INFO MainThread:476 [wandb_setup.py:_flush():76] Current SDK version is 0.16.1
|
2 |
+
2024-01-07 11:34:44,806 INFO MainThread:476 [wandb_setup.py:_flush():76] Configure stats pid to 476
|
3 |
+
2024-01-07 11:34:44,806 INFO MainThread:476 [wandb_setup.py:_flush():76] Loading settings from /root/.config/wandb/settings
|
4 |
+
2024-01-07 11:34:44,807 INFO MainThread:476 [wandb_setup.py:_flush():76] Loading settings from /content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/wandb/settings
|
5 |
+
2024-01-07 11:34:44,807 INFO MainThread:476 [wandb_setup.py:_flush():76] Loading settings from environment variables: {}
|
6 |
+
2024-01-07 11:34:44,807 INFO MainThread:476 [wandb_setup.py:_flush():76] Applying setup settings: {'_disable_service': False}
|
7 |
+
2024-01-07 11:34:44,807 INFO MainThread:476 [wandb_setup.py:_flush():76] Inferring run settings from compute environment: {'program': '<python with no main file>'}
|
8 |
+
2024-01-07 11:34:44,807 ERROR MainThread:476 [wandb_setup.py:_flush():76] error
|
9 |
+
Traceback (most recent call last):
|
10 |
+
File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_init.py", line 1166, in init
|
11 |
+
wi.setup(kwargs)
|
12 |
+
File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_init.py", line 306, in setup
|
13 |
+
wandb_login._login(
|
14 |
+
File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_login.py", line 298, in _login
|
15 |
+
wlogin.prompt_api_key()
|
16 |
+
File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_login.py", line 221, in prompt_api_key
|
17 |
+
key, status = self._prompt_api_key()
|
18 |
+
File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_login.py", line 201, in _prompt_api_key
|
19 |
+
key = apikey.prompt_api_key(
|
20 |
+
File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/apikey.py", line 144, in prompt_api_key
|
21 |
+
key = input_callback(api_ask).strip()
|
22 |
+
File "/usr/local/lib/python3.10/dist-packages/click/termui.py", line 164, in prompt
|
23 |
+
value = prompt_func(prompt)
|
24 |
+
File "/usr/local/lib/python3.10/dist-packages/click/termui.py", line 147, in prompt_func
|
25 |
+
raise Abort() from None
|
26 |
+
click.exceptions.Abort
|
27 |
+
2024-01-07 11:34:44,807 INFO MainThread:476 [wandb_setup.py:_flush():76] Applying login settings: {'api_key': '***REDACTED***'}
|
28 |
+
2024-01-07 11:34:44,808 INFO MainThread:476 [wandb_init.py:_log_setup():524] Logging user logs to /content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/wandb/run-20240107_113444-ebd79hle/logs/debug.log
|
29 |
+
2024-01-07 11:34:44,808 INFO MainThread:476 [wandb_init.py:_log_setup():525] Logging internal logs to /content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/wandb/run-20240107_113444-ebd79hle/logs/debug-internal.log
|
30 |
+
2024-01-07 11:34:44,809 INFO MainThread:476 [wandb_init.py:_jupyter_setup():470] configuring jupyter hooks <wandb.sdk.wandb_init._WandbInit object at 0x7c7dab76c8b0>
|
31 |
+
2024-01-07 11:34:44,809 INFO MainThread:476 [wandb_init.py:init():564] calling init triggers
|
32 |
+
2024-01-07 11:34:44,809 INFO MainThread:476 [wandb_init.py:init():571] wandb.init called with sweep_config: {}
|
33 |
+
config: {}
|
34 |
+
2024-01-07 11:34:44,810 INFO MainThread:476 [wandb_init.py:init():614] starting backend
|
35 |
+
2024-01-07 11:34:44,810 INFO MainThread:476 [wandb_init.py:init():618] setting up manager
|
36 |
+
2024-01-07 11:34:44,815 INFO MainThread:476 [backend.py:_multiprocessing_setup():105] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
|
37 |
+
2024-01-07 11:34:44,817 INFO MainThread:476 [wandb_init.py:init():624] backend started and connected
|
38 |
+
2024-01-07 11:34:44,842 INFO MainThread:476 [wandb_run.py:_label_probe_notebook():1294] probe notebook
|
39 |
+
2024-01-07 11:34:47,220 INFO MainThread:476 [wandb_init.py:init():716] updated telemetry
|
40 |
+
2024-01-07 11:34:47,236 INFO MainThread:476 [wandb_init.py:init():749] communicating run to backend with 90.0 second timeout
|
41 |
+
2024-01-07 11:34:47,619 INFO MainThread:476 [wandb_run.py:_on_init():2254] communicating current version
|
42 |
+
2024-01-07 11:34:47,757 INFO MainThread:476 [wandb_run.py:_on_init():2263] got version response
|
43 |
+
2024-01-07 11:34:47,758 INFO MainThread:476 [wandb_init.py:init():800] starting run threads in backend
|
44 |
+
2024-01-07 11:34:47,846 INFO MainThread:476 [wandb_run.py:_console_start():2233] atexit reg
|
45 |
+
2024-01-07 11:34:47,846 INFO MainThread:476 [wandb_run.py:_redirect():2088] redirect: wrap_raw
|
46 |
+
2024-01-07 11:34:47,846 INFO MainThread:476 [wandb_run.py:_redirect():2153] Wrapping output streams.
|
47 |
+
2024-01-07 11:34:47,846 INFO MainThread:476 [wandb_run.py:_redirect():2178] Redirects installed.
|
48 |
+
2024-01-07 11:34:47,848 INFO MainThread:476 [wandb_init.py:init():841] run started, returning control to user process
|
49 |
+
2024-01-07 11:34:47,851 INFO MainThread:476 [wandb_run.py:_config_callback():1342] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': 4096, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 10000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'chunk_size_feed_forward': 0, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': None, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'mistralai/Mistral-7B-v0.1', 'transformers_version': '4.36.2', 'model_type': 'mistral', 'quantization_config': {'quant_method': 'QuantizationMethod.BITS_AND_BYTES', 'load_in_8bit': False, 'load_in_4bit': True, 'llm_int8_threshold': 6.0, 'llm_int8_skip_modules': None, 'llm_int8_enable_fp32_cpu_offload': False, 'llm_int8_has_fp16_weight': False, 'bnb_4bit_quant_type': 'nf4', 'bnb_4bit_use_double_quant': True, 'bnb_4bit_compute_dtype': 'bfloat16'}, 'output_dir': '/content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': False, 'do_predict': False, 'evaluation_strategy': 'no', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 8, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 2, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 0.3, 'num_train_epochs': 3.0, 'max_steps': 60, 'lr_scheduler_type': 'cosine', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.03, 'warmup_steps': 0, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance/runs/Jan07_11-26-45_371ca9b7a7c7', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 10, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 10, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': False, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': False, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'past_index': -1, 'run_name': '/content/gdrive/MyDrive/LLM/Mistral-7B-Finetuning-Insurance', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': False, 'metric_for_best_model': None, 'greater_is_better': None, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_32bit', 'optim_args': None, 'adafactor': False, 'group_by_length': True, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': False, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
|
50 |
+
2024-01-07 11:47:19,157 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
51 |
+
2024-01-07 11:47:19,158 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
52 |
+
2024-01-07 11:47:27,617 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
53 |
+
2024-01-07 11:47:36,404 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
54 |
+
2024-01-07 11:47:36,404 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
55 |
+
2024-01-07 11:47:44,924 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
56 |
+
2024-01-07 11:48:59,908 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
57 |
+
2024-01-07 11:48:59,908 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
58 |
+
2024-01-07 11:49:02,615 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
59 |
+
2024-01-07 11:50:30,938 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
60 |
+
2024-01-07 11:50:30,938 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
61 |
+
2024-01-07 11:50:51,024 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
62 |
+
2024-01-07 11:50:51,029 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
63 |
+
2024-01-07 11:50:51,029 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
64 |
+
2024-01-07 11:50:58,161 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
65 |
+
2024-01-07 11:51:45,068 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
66 |
+
2024-01-07 11:51:45,069 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
67 |
+
2024-01-07 11:51:56,171 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
68 |
+
2024-01-07 11:52:39,110 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
69 |
+
2024-01-07 11:52:39,111 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
70 |
+
2024-01-07 11:53:01,893 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
71 |
+
2024-01-07 11:53:56,080 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
72 |
+
2024-01-07 11:53:56,081 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
73 |
+
2024-01-07 11:54:05,594 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
74 |
+
2024-01-07 11:54:58,983 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
75 |
+
2024-01-07 11:54:58,983 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
76 |
+
2024-01-07 11:55:17,221 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
77 |
+
2024-01-07 11:56:16,502 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
78 |
+
2024-01-07 11:56:16,503 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
79 |
+
2024-01-07 11:59:32,174 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
80 |
+
2024-01-07 12:00:37,545 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
81 |
+
2024-01-07 12:00:37,545 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
82 |
+
2024-01-07 12:00:49,673 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
83 |
+
2024-01-07 12:02:04,679 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
84 |
+
2024-01-07 12:02:04,679 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
85 |
+
2024-01-07 12:02:42,745 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
86 |
+
2024-01-07 12:03:47,588 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
87 |
+
2024-01-07 12:03:47,588 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
88 |
+
2024-01-07 12:04:07,606 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
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+
2024-01-07 12:05:30,225 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
90 |
+
2024-01-07 12:05:30,225 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
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+
2024-01-07 12:05:51,525 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
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+
2024-01-07 12:06:45,821 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
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+
2024-01-07 12:06:45,822 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
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+
2024-01-07 12:08:31,068 INFO MainThread:476 [wandb_init.py:_resume_backend():440] resuming backend
|
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+
2024-01-07 12:09:26,049 INFO MainThread:476 [jupyter.py:save_ipynb():373] not saving jupyter notebook
|
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+
2024-01-07 12:09:26,049 INFO MainThread:476 [wandb_init.py:_pause_backend():435] pausing backend
|
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+
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resume_from_checkpoint:
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596 |
+
desc: null
|
597 |
+
value: null
|
598 |
+
hub_model_id:
|
599 |
+
desc: null
|
600 |
+
value: null
|
601 |
+
hub_strategy:
|
602 |
+
desc: null
|
603 |
+
value: every_save
|
604 |
+
hub_token:
|
605 |
+
desc: null
|
606 |
+
value: <HUB_TOKEN>
|
607 |
+
hub_private_repo:
|
608 |
+
desc: null
|
609 |
+
value: false
|
610 |
+
hub_always_push:
|
611 |
+
desc: null
|
612 |
+
value: false
|
613 |
+
gradient_checkpointing:
|
614 |
+
desc: null
|
615 |
+
value: false
|
616 |
+
gradient_checkpointing_kwargs:
|
617 |
+
desc: null
|
618 |
+
value: null
|
619 |
+
include_inputs_for_metrics:
|
620 |
+
desc: null
|
621 |
+
value: false
|
622 |
+
fp16_backend:
|
623 |
+
desc: null
|
624 |
+
value: auto
|
625 |
+
push_to_hub_model_id:
|
626 |
+
desc: null
|
627 |
+
value: null
|
628 |
+
push_to_hub_organization:
|
629 |
+
desc: null
|
630 |
+
value: null
|
631 |
+
push_to_hub_token:
|
632 |
+
desc: null
|
633 |
+
value: <PUSH_TO_HUB_TOKEN>
|
634 |
+
mp_parameters:
|
635 |
+
desc: null
|
636 |
+
value: ''
|
637 |
+
auto_find_batch_size:
|
638 |
+
desc: null
|
639 |
+
value: false
|
640 |
+
full_determinism:
|
641 |
+
desc: null
|
642 |
+
value: false
|
643 |
+
torchdynamo:
|
644 |
+
desc: null
|
645 |
+
value: null
|
646 |
+
ray_scope:
|
647 |
+
desc: null
|
648 |
+
value: last
|
649 |
+
ddp_timeout:
|
650 |
+
desc: null
|
651 |
+
value: 1800
|
652 |
+
torch_compile:
|
653 |
+
desc: null
|
654 |
+
value: false
|
655 |
+
torch_compile_backend:
|
656 |
+
desc: null
|
657 |
+
value: null
|
658 |
+
torch_compile_mode:
|
659 |
+
desc: null
|
660 |
+
value: null
|
661 |
+
dispatch_batches:
|
662 |
+
desc: null
|
663 |
+
value: null
|
664 |
+
split_batches:
|
665 |
+
desc: null
|
666 |
+
value: null
|
667 |
+
include_tokens_per_second:
|
668 |
+
desc: null
|
669 |
+
value: false
|
670 |
+
include_num_input_tokens_seen:
|
671 |
+
desc: null
|
672 |
+
value: false
|
673 |
+
neftune_noise_alpha:
|
674 |
+
desc: null
|
675 |
+
value: null
|
676 |
+
optim_target_modules:
|
677 |
+
desc: null
|
678 |
+
value: null
|
wandb/run-20240321_015458-y11xrjxv/files/output.log
ADDED
@@ -0,0 +1,81 @@
|
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|
|
|
|
1 |
+
-------------------------------------------------
|
2 |
+
Pre-trained Model Answer:
|
3 |
+
Answer the following question truthfully.
|
4 |
+
: 고지의무에 대해 상세하게 알려줘
|
5 |
+
: 10분이내로 답변을 보냄으로서, 당신은 그것들을 읽었다는 사실을 인정한다.
|
6 |
+
```python
|
7 |
+
import sys
|
8 |
+
sys.stdin = open('input_2587.txt')
|
9 |
+
# input()를 통해 입력받기
|
10 |
+
T=int(input()) # T개의 테스트 데이터가 주어진다.
|
11 |
+
for tc in range(1,T+1):
|
12 |
+
N,M=map(str,input().split())
|
13 |
+
print('#{} {}'.format(tc,(N*3)+((len(M)-1)*4)))
|
14 |
+
```
|
15 |
+
- `print("#{}. {}".format(tc,(N*3) + ((len(M)) - 1)*4), end='\n' )`
|
16 |
+
출력문을 작성할때 \n 없애면 줄바꿈되지않음!
|
17 |
+
## 풀이방법
|
18 |
+
### 첫번째 시도 (오류발생)
|
19 |
+
```python
|
20 |
+
def solution
|
21 |
+
-------------------------------------------------
|
22 |
+
Finetuning PEFT Model Answer:
|
23 |
+
Answer the following question truthfully.
|
24 |
+
: 고지의무에 대해 상세하게 알려줘
|
25 |
+
: 고지의무란, 법인이나 개인사업자가 특정한 경우를 제외시키는 바람직한 행위로서 그러한 경우에 관련된 내용을 공식적으로 통보할 것임을 약속함과 같은 일종의 규정입니다. 예) 주민등록번호변경 및 성별수정 등 신분증 발급 후 10일 안에 국토교통부 소견서 확인 필요(고지의무), 허가기간동안 운전면탈 또는 차량 파기 등 중도 취소 불가능한 계약 체결 시 24시간 안에 연구원장 본인 또는 담당자와 만남 (고지의무). 단, 고지의무 없어야 되는 경우라면 반드
|
26 |
+
-------------------------------------------------
|
27 |
+
-------------------------------------------------
|
28 |
+
Pre-trained Model Answer:
|
29 |
+
Answer the following question truthfully.
|
30 |
+
: 골프보험 알려줘
|
31 |
+
: 10분전에 맞는다고 했으니까 그때부터 시작한다.
|
32 |
+
: 25년이나 지난 것도 아직 안해서...
|
33 |
+
: 36개월은 48개월의 반이라고 생각하면 된다.
|
34 |
+
: 어차피 내가 할일인데, 너무 바쁜거야?
|
35 |
+
: 사람들을 위해 노력하자!
|
36 |
+
: 오랜만에 같이 있었네요~
|
37 |
+
: 저기 우리집 주변엔 여러 식당이 있습니다.
|
38 |
+
: 제발 말로 설명해줄래요?
|
39 |
+
: 정말 잘 모르겠구나..
|
40 |
+
: 대체 누군가를 찾았더라!!
|
41 |
+
: 미국에선 물건을 받게되면 항상 감사합니다 라고 표현하는 경향이
|
42 |
+
-------------------------------------------------
|
43 |
+
Finetuning PEFT Model Answer:
|
44 |
+
Answer the following question truthfully.
|
45 |
+
: 골프보험 알려줘
|
46 |
+
: 골프보험은 자동차보험과는 다른 종류의 보험입니다. 그러나, 대부분의 경우에서 자동차를 이용하여 운행을 한 후 골프장으로 가고 있거나 골프장에서 돌아오던 중 사고가 발생했기 때문에 자동차보험으로도 처리할 수 없습니다. 따라서 골프보험이 필요합니다. 또한 골프장내에서 일반적인 물건실제상해(예: 화재)와 관련된 것들까지 포함되어 있습니다. 단, 주민등록증 번호가 같은 가구간 집안원 및 외국인 비회사직업 개인은 공통의 법정
|
47 |
+
-------------------------------------------------
|
48 |
+
-------------------------------------------------
|
49 |
+
Pre-trained Model Answer:
|
50 |
+
Answer the following question truthfully.
|
51 |
+
: 사망보험에 대하여 알려줘
|
52 |
+
: 10분이내로 답변해주세요!
|
53 |
+
## Question
|
54 |
+
### What is life insurance?
|
55 |
+
Life Insurance, also known as Life Assurance or Death Benefit in some countries, provides a lump sum payment to your beneficiaries upon death of an insured person (the policyholder). The amount paid out by the company depends on how much you have agreed with them beforehand and what type of plan they offer; there are many different types available so it’s important that we understand all our options when choosing one for ourselves/our families etcetera…
|
56 |
+
The most common form would be whole-life policies which provide coverage until either age 65+ years old OR after passing away whichever comes first – this means if someone dies at any point during their lifetime then no matter where he was living nor whether his family members were still alive themselves too because these things don't affect anything else about him except maybe making sure everything goes smoothly without problems arising due lack knowledge regarding such matters...
|
57 |
+
-------------------------------------------------
|
58 |
+
Finetuning PEFT Model Answer:
|
59 |
+
Answer the following question truthfully.
|
60 |
+
: 사망보험에 대하여 알려줘
|
61 |
+
: 사망보험은 자동차보험과는 다른 종류의 보험입니다. 그러나, 이를 포함한 모든 보험을 일반적으로 ‘보험’이라고 부르기도 합니다. 또한 생명보험(인수형)과 같습니다. 사망보험은 가입시점에서 지정된 금액만큼 상속받게 되어있거나 특별히 약관에 따라 제공될 경우 해당 금액을 계산할 때 주로 사용됩니다. 예를들면 100만원, 250만원, 3천만원등 각각의 금액을 선택할 수 있습니다. 단, 최소 100만원~최대 4천만원까지 설치할 수
|
62 |
+
-------------------------------------------------
|
63 |
+
-------------------------------------------------
|
64 |
+
Pre-trained Model Answer:
|
65 |
+
Answer the following question truthfully.
|
66 |
+
: 선물이 뭐야?
|
67 |
+
: 책, 휴대전화, 가방, 노트북, 스마트워치, 음식, 의류, 기타
|
68 |
+
Answer the following questions with a number from 1 to 5 (1 is lowest and 5 is highest).
|
69 |
+
: How much do you like this gift?
|
70 |
+
: ______
|
71 |
+
: What kind of person would give such gifts as these?
|
72 |
+
: _______
|
73 |
+
: Which one(s) are your favorite among them all? Why?
|
74 |
+
: ____________
|
75 |
+
: If someone gave me any of those things I'd be happy about it because...
|
76 |
+
: _________________
|
77 |
+
-------------------------------------------------
|
78 |
+
Finetuning PEFT Model Answer:
|
79 |
+
Answer the following question truthfully.
|
80 |
+
: 선물이 뭐야?
|
81 |
+
: 옵션은 미래가치를 기반으로 하는 상품입니다. 즉, 미래에서의 시장을 예견해보고자 합니다. 그러나 선물은 현재와 같은 상태로 지정된 일정한 수량과 종류의 제품(주식, 화학물질)을 특별히 거래할 것인데요. 또한 매도/구매 계약의 성립 및 만료까지 남아있는 날짜를 말합니다. 단순히 흔히 사용되어진 ‘미래’라는 표현을 생각했더라면 오답입니다! 실제로 선물은 미래가치를 포함하여 현금 등급 중 최저 등급부터 10년 후까지 미래가치를 추산하며 판매됩니다. 따
|
wandb/run-20240321_015458-y11xrjxv/files/requirements.txt
ADDED
@@ -0,0 +1,510 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
Babel==2.14.0
|
2 |
+
CacheControl==0.14.0
|
3 |
+
Cython==3.0.9
|
4 |
+
Flask==2.2.5
|
5 |
+
GDAL==3.6.4
|
6 |
+
GitPython==3.1.42
|
7 |
+
Jinja2==3.1.3
|
8 |
+
Markdown==3.6
|
9 |
+
MarkupSafe==2.1.5
|
10 |
+
Pillow==9.4.0
|
11 |
+
PyDrive2==1.6.3
|
12 |
+
PyDrive==1.3.1
|
13 |
+
PyGObject==3.42.1
|
14 |
+
PyJWT==2.3.0
|
15 |
+
PyOpenGL==3.1.7
|
16 |
+
PySocks==1.7.1
|
17 |
+
PyWavelets==1.5.0
|
18 |
+
PyYAML==6.0.1
|
19 |
+
Pygments==2.16.1
|
20 |
+
SQLAlchemy==2.0.28
|
21 |
+
SecretStorage==3.3.1
|
22 |
+
Send2Trash==1.8.2
|
23 |
+
Sphinx==5.0.2
|
24 |
+
Werkzeug==3.0.1
|
25 |
+
absl-py==1.4.0
|
26 |
+
accelerate==0.28.0
|
27 |
+
aiohttp==3.9.3
|
28 |
+
aiosignal==1.3.1
|
29 |
+
alabaster==0.7.16
|
30 |
+
albumentations==1.3.1
|
31 |
+
altair==4.2.2
|
32 |
+
annotated-types==0.6.0
|
33 |
+
anyio==3.7.1
|
34 |
+
appdirs==1.4.4
|
35 |
+
argon2-cffi-bindings==21.2.0
|
36 |
+
argon2-cffi==23.1.0
|
37 |
+
array-record==0.5.0
|
38 |
+
arviz==0.15.1
|
39 |
+
astropy==5.3.4
|
40 |
+
astunparse==1.6.3
|
41 |
+
async-timeout==4.0.3
|
42 |
+
atpublic==4.0
|
43 |
+
attrs==23.2.0
|
44 |
+
audioread==3.0.1
|
45 |
+
autograd==1.6.2
|
46 |
+
backcall==0.2.0
|
47 |
+
beautifulsoup4==4.12.3
|
48 |
+
bidict==0.23.1
|
49 |
+
bigframes==0.25.0
|
50 |
+
bitsandbytes==0.43.0
|
51 |
+
bleach==6.1.0
|
52 |
+
blinker==1.4
|
53 |
+
blis==0.7.11
|
54 |
+
blosc2==2.0.0
|
55 |
+
bokeh==3.3.4
|
56 |
+
bqplot==0.12.43
|
57 |
+
branca==0.7.1
|
58 |
+
build==1.1.1
|
59 |
+
cachetools==5.3.3
|
60 |
+
catalogue==2.0.10
|
61 |
+
certifi==2024.2.2
|
62 |
+
cffi==1.16.0
|
63 |
+
chardet==5.2.0
|
64 |
+
charset-normalizer==3.3.2
|
65 |
+
chex==0.1.85
|
66 |
+
click-plugins==1.1.1
|
67 |
+
click==8.1.7
|
68 |
+
cligj==0.7.2
|
69 |
+
cloudpathlib==0.16.0
|
70 |
+
cloudpickle==2.2.1
|
71 |
+
cmake==3.27.9
|
72 |
+
cmdstanpy==1.2.1
|
73 |
+
colorcet==3.1.0
|
74 |
+
colorlover==0.3.0
|
75 |
+
colour==0.1.5
|
76 |
+
community==1.0.0b1
|
77 |
+
confection==0.1.4
|
78 |
+
cons==0.4.6
|
79 |
+
contextlib2==21.6.0
|
80 |
+
contourpy==1.2.0
|
81 |
+
cryptography==42.0.5
|
82 |
+
cufflinks==0.17.3
|
83 |
+
cupy-cuda12x==12.2.0
|
84 |
+
cvxopt==1.3.2
|
85 |
+
cvxpy==1.3.3
|
86 |
+
cycler==0.12.1
|
87 |
+
cymem==2.0.8
|
88 |
+
dask==2023.8.1
|
89 |
+
datascience==0.17.6
|
90 |
+
datasets==2.18.0
|
91 |
+
db-dtypes==1.2.0
|
92 |
+
dbus-python==1.2.18
|
93 |
+
debugpy==1.6.6
|
94 |
+
decorator==4.4.2
|
95 |
+
defusedxml==0.7.1
|
96 |
+
dill==0.3.8
|
97 |
+
distributed==2023.8.1
|
98 |
+
distro==1.7.0
|
99 |
+
dlib==19.24.2
|
100 |
+
dm-tree==0.1.8
|
101 |
+
docker-pycreds==0.4.0
|
102 |
+
docstring_parser==0.16
|
103 |
+
docutils==0.18.1
|
104 |
+
dopamine-rl==4.0.6
|
105 |
+
duckdb==0.9.2
|
106 |
+
earthengine-api==0.1.394
|
107 |
+
easydict==1.13
|
108 |
+
ecos==2.0.13
|
109 |
+
editdistance==0.6.2
|
110 |
+
eerepr==0.0.4
|
111 |
+
einops==0.7.0
|
112 |
+
en-core-web-sm==3.7.1
|
113 |
+
entrypoints==0.4
|
114 |
+
et-xmlfile==1.1.0
|
115 |
+
etils==1.7.0
|
116 |
+
etuples==0.3.9
|
117 |
+
exceptiongroup==1.2.0
|
118 |
+
fastai==2.7.14
|
119 |
+
fastcore==1.5.29
|
120 |
+
fastdownload==0.0.7
|
121 |
+
fastjsonschema==2.19.1
|
122 |
+
fastprogress==1.0.3
|
123 |
+
fastrlock==0.8.2
|
124 |
+
filelock==3.13.1
|
125 |
+
fiona==1.9.6
|
126 |
+
firebase-admin==5.3.0
|
127 |
+
flatbuffers==24.3.7
|
128 |
+
flax==0.8.2
|
129 |
+
folium==0.14.0
|
130 |
+
fonttools==4.49.0
|
131 |
+
frozendict==2.4.0
|
132 |
+
frozenlist==1.4.1
|
133 |
+
fsspec==2023.6.0
|
134 |
+
future==0.18.3
|
135 |
+
gast==0.5.4
|
136 |
+
gcsfs==2023.6.0
|
137 |
+
gdown==4.7.3
|
138 |
+
geemap==0.32.0
|
139 |
+
gensim==4.3.2
|
140 |
+
geocoder==1.38.1
|
141 |
+
geographiclib==2.0
|
142 |
+
geopandas==0.13.2
|
143 |
+
geopy==2.3.0
|
144 |
+
gin-config==0.5.0
|
145 |
+
gitdb==4.0.11
|
146 |
+
glob2==0.7
|
147 |
+
google-ai-generativelanguage==0.4.0
|
148 |
+
google-api-core==2.11.1
|
149 |
+
google-api-python-client==2.84.0
|
150 |
+
google-auth-httplib2==0.1.1
|
151 |
+
google-auth-oauthlib==1.2.0
|
152 |
+
google-auth==2.27.0
|
153 |
+
google-cloud-aiplatform==1.44.0
|
154 |
+
google-cloud-bigquery-connection==1.12.1
|
155 |
+
google-cloud-bigquery-storage==2.24.0
|
156 |
+
google-cloud-bigquery==3.12.0
|
157 |
+
google-cloud-core==2.3.3
|
158 |
+
google-cloud-datastore==2.15.2
|
159 |
+
google-cloud-firestore==2.11.1
|
160 |
+
google-cloud-functions==1.13.3
|
161 |
+
google-cloud-iam==2.14.3
|
162 |
+
google-cloud-language==2.13.3
|
163 |
+
google-cloud-resource-manager==1.12.3
|
164 |
+
google-cloud-storage==2.8.0
|
165 |
+
google-cloud-translate==3.11.3
|
166 |
+
google-colab==1.0.0
|
167 |
+
google-crc32c==1.5.0
|
168 |
+
google-generativeai==0.3.2
|
169 |
+
google-pasta==0.2.0
|
170 |
+
google-resumable-media==2.7.0
|
171 |
+
google==2.0.3
|
172 |
+
googleapis-common-protos==1.63.0
|
173 |
+
googledrivedownloader==0.4
|
174 |
+
graphviz==0.20.1
|
175 |
+
greenlet==3.0.3
|
176 |
+
grpc-google-iam-v1==0.13.0
|
177 |
+
grpcio-status==1.48.2
|
178 |
+
grpcio==1.62.1
|
179 |
+
gspread-dataframe==3.3.1
|
180 |
+
gspread==3.4.2
|
181 |
+
gym-notices==0.0.8
|
182 |
+
gym==0.25.2
|
183 |
+
h5netcdf==1.3.0
|
184 |
+
h5py==3.9.0
|
185 |
+
holidays==0.44
|
186 |
+
holoviews==1.17.1
|
187 |
+
html5lib==1.1
|
188 |
+
httpimport==1.3.1
|
189 |
+
httplib2==0.22.0
|
190 |
+
huggingface-hub==0.20.3
|
191 |
+
humanize==4.7.0
|
192 |
+
hyperopt==0.2.7
|
193 |
+
ibis-framework==8.0.0
|
194 |
+
idna==3.6
|
195 |
+
imageio-ffmpeg==0.4.9
|
196 |
+
imageio==2.31.6
|
197 |
+
imagesize==1.4.1
|
198 |
+
imbalanced-learn==0.10.1
|
199 |
+
imgaug==0.4.0
|
200 |
+
importlib_metadata==7.0.2
|
201 |
+
importlib_resources==6.3.0
|
202 |
+
imutils==0.5.4
|
203 |
+
inflect==7.0.0
|
204 |
+
iniconfig==2.0.0
|
205 |
+
intel-openmp==2023.2.4
|
206 |
+
ipyevents==2.0.2
|
207 |
+
ipyfilechooser==0.6.0
|
208 |
+
ipykernel==5.5.6
|
209 |
+
ipyleaflet==0.18.2
|
210 |
+
ipython-genutils==0.2.0
|
211 |
+
ipython-sql==0.5.0
|
212 |
+
ipython==7.34.0
|
213 |
+
ipytree==0.2.2
|
214 |
+
ipywidgets==7.7.1
|
215 |
+
itsdangerous==2.1.2
|
216 |
+
jax==0.4.23
|
217 |
+
jaxlib==0.4.23+cuda12.cudnn89
|
218 |
+
jeepney==0.7.1
|
219 |
+
jieba==0.42.1
|
220 |
+
joblib==1.3.2
|
221 |
+
jsonpickle==3.0.3
|
222 |
+
jsonschema-specifications==2023.12.1
|
223 |
+
jsonschema==4.19.2
|
224 |
+
jupyter-client==6.1.12
|
225 |
+
jupyter-console==6.1.0
|
226 |
+
jupyter-server==1.24.0
|
227 |
+
jupyter_core==5.7.2
|
228 |
+
jupyterlab_pygments==0.3.0
|
229 |
+
jupyterlab_widgets==3.0.10
|
230 |
+
kaggle==1.5.16
|
231 |
+
kagglehub==0.2.0
|
232 |
+
keras==2.15.0
|
233 |
+
keyring==23.5.0
|
234 |
+
kiwisolver==1.4.5
|
235 |
+
langcodes==3.3.0
|
236 |
+
launchpadlib==1.10.16
|
237 |
+
lazr.restfulclient==0.14.4
|
238 |
+
lazr.uri==1.0.6
|
239 |
+
lazy_loader==0.3
|
240 |
+
libclang==16.0.6
|
241 |
+
librosa==0.10.1
|
242 |
+
lightgbm==4.1.0
|
243 |
+
linkify-it-py==2.0.3
|
244 |
+
llvmlite==0.41.1
|
245 |
+
locket==1.0.0
|
246 |
+
logical-unification==0.4.6
|
247 |
+
lxml==4.9.4
|
248 |
+
malloy==2023.1067
|
249 |
+
markdown-it-py==3.0.0
|
250 |
+
matplotlib-inline==0.1.6
|
251 |
+
matplotlib-venn==0.11.10
|
252 |
+
matplotlib==3.7.1
|
253 |
+
mdit-py-plugins==0.4.0
|
254 |
+
mdurl==0.1.2
|
255 |
+
miniKanren==1.0.3
|
256 |
+
missingno==0.5.2
|
257 |
+
mistune==0.8.4
|
258 |
+
mizani==0.9.3
|
259 |
+
mkl==2023.2.0
|
260 |
+
ml-dtypes==0.2.0
|
261 |
+
mlxtend==0.22.0
|
262 |
+
more-itertools==10.1.0
|
263 |
+
moviepy==1.0.3
|
264 |
+
mpmath==1.3.0
|
265 |
+
msgpack==1.0.8
|
266 |
+
multidict==6.0.5
|
267 |
+
multipledispatch==1.0.0
|
268 |
+
multiprocess==0.70.16
|
269 |
+
multitasking==0.0.11
|
270 |
+
murmurhash==1.0.10
|
271 |
+
music21==9.1.0
|
272 |
+
natsort==8.4.0
|
273 |
+
nbclassic==1.0.0
|
274 |
+
nbclient==0.10.0
|
275 |
+
nbconvert==6.5.4
|
276 |
+
nbformat==5.10.2
|
277 |
+
nest-asyncio==1.6.0
|
278 |
+
networkx==3.2.1
|
279 |
+
nibabel==4.0.2
|
280 |
+
nltk==3.8.1
|
281 |
+
notebook==6.5.5
|
282 |
+
notebook_shim==0.2.4
|
283 |
+
numba==0.58.1
|
284 |
+
numexpr==2.9.0
|
285 |
+
numpy==1.25.2
|
286 |
+
nvidia-cublas-cu12==12.1.3.1
|
287 |
+
nvidia-cuda-cupti-cu12==12.1.105
|
288 |
+
nvidia-cuda-nvrtc-cu12==12.1.105
|
289 |
+
nvidia-cuda-runtime-cu12==12.1.105
|
290 |
+
nvidia-cudnn-cu12==8.9.2.26
|
291 |
+
nvidia-cufft-cu12==11.0.2.54
|
292 |
+
nvidia-curand-cu12==10.3.2.106
|
293 |
+
nvidia-cusolver-cu12==11.4.5.107
|
294 |
+
nvidia-cusparse-cu12==12.1.0.106
|
295 |
+
nvidia-nccl-cu12==2.19.3
|
296 |
+
nvidia-nvjitlink-cu12==12.4.99
|
297 |
+
nvidia-nvtx-cu12==12.1.105
|
298 |
+
oauth2client==4.1.3
|
299 |
+
oauthlib==3.2.2
|
300 |
+
opencv-contrib-python==4.8.0.76
|
301 |
+
opencv-python-headless==4.9.0.80
|
302 |
+
opencv-python==4.8.0.76
|
303 |
+
openpyxl==3.1.2
|
304 |
+
opt-einsum==3.3.0
|
305 |
+
optax==0.2.1
|
306 |
+
orbax-checkpoint==0.4.4
|
307 |
+
osqp==0.6.2.post8
|
308 |
+
packaging==24.0
|
309 |
+
pandas-datareader==0.10.0
|
310 |
+
pandas-gbq==0.19.2
|
311 |
+
pandas-stubs==1.5.3.230304
|
312 |
+
pandas==1.5.3
|
313 |
+
pandocfilters==1.5.1
|
314 |
+
panel==1.3.8
|
315 |
+
param==2.0.2
|
316 |
+
parso==0.8.3
|
317 |
+
parsy==2.1
|
318 |
+
partd==1.4.1
|
319 |
+
pathlib==1.0.1
|
320 |
+
patsy==0.5.6
|
321 |
+
peewee==3.17.1
|
322 |
+
peft==0.9.1.dev0
|
323 |
+
pexpect==4.9.0
|
324 |
+
pickleshare==0.7.5
|
325 |
+
pip-tools==6.13.0
|
326 |
+
pip==23.1.2
|
327 |
+
platformdirs==4.2.0
|
328 |
+
plotly==5.15.0
|
329 |
+
plotnine==0.12.4
|
330 |
+
pluggy==1.4.0
|
331 |
+
polars==0.20.2
|
332 |
+
pooch==1.8.1
|
333 |
+
portpicker==1.5.2
|
334 |
+
prefetch-generator==1.0.3
|
335 |
+
preshed==3.0.9
|
336 |
+
prettytable==3.10.0
|
337 |
+
proglog==0.1.10
|
338 |
+
progressbar2==4.2.0
|
339 |
+
prometheus_client==0.20.0
|
340 |
+
promise==2.3
|
341 |
+
prompt-toolkit==3.0.43
|
342 |
+
prophet==1.1.5
|
343 |
+
proto-plus==1.23.0
|
344 |
+
protobuf==3.20.3
|
345 |
+
psutil==5.9.5
|
346 |
+
psycopg2==2.9.9
|
347 |
+
ptyprocess==0.7.0
|
348 |
+
py-cpuinfo==9.0.0
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wandb/run-20240321_015458-y11xrjxv/run-y11xrjxv.wandb
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wandb/run-20240322_043407-hize5f4p/files/config.yaml
ADDED
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1 |
+
wandb_version: 1
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2 |
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|
3 |
+
_wandb:
|
4 |
+
desc: null
|
5 |
+
value:
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6 |
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python_version: 3.10.12
|
7 |
+
cli_version: 0.16.4
|
8 |
+
framework: huggingface
|
9 |
+
huggingface_version: 4.39.0
|
10 |
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is_jupyter_run: true
|
11 |
+
is_kaggle_kernel: false
|
12 |
+
start_time: 1711082047.0
|
13 |
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t:
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514 |
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515 |
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greater_is_better:
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517 |
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518 |
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ignore_data_skip:
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520 |
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fsdp:
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523 |
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524 |
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fsdp_min_num_params:
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fsdp_config:
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529 |
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530 |
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534 |
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xla_fsdp_grad_ckpt: false
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535 |
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fsdp_transformer_layer_cls_to_wrap:
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536 |
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537 |
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538 |
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accelerator_config:
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539 |
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540 |
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542 |
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even_batches: true
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544 |
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deepspeed:
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546 |
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label_smoothing_factor:
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549 |
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optim:
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552 |
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553 |
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value: paged_adamw_32bit
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optim_args:
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555 |
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556 |
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557 |
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adafactor:
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558 |
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559 |
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560 |
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group_by_length:
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561 |
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562 |
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length_column_name:
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564 |
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565 |
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566 |
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report_to:
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567 |
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value:
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570 |
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|
571 |
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ddp_find_unused_parameters:
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572 |
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573 |
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ddp_bucket_cap_mb:
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575 |
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ddp_broadcast_buffers:
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578 |
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579 |
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dataloader_pin_memory:
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581 |
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|
582 |
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dataloader_persistent_workers:
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584 |
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|
585 |
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586 |
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skip_memory_metrics:
|
587 |
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588 |
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|
589 |
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use_legacy_prediction_loop:
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590 |
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desc: null
|
591 |
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|
592 |
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push_to_hub:
|
593 |
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desc: null
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594 |
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595 |
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resume_from_checkpoint:
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596 |
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597 |
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598 |
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hub_model_id:
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599 |
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desc: null
|
600 |
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601 |
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hub_strategy:
|
602 |
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desc: null
|
603 |
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value: every_save
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hub_token:
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605 |
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|
606 |
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value: <HUB_TOKEN>
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607 |
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hub_private_repo:
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608 |
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609 |
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value: false
|
610 |
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hub_always_push:
|
611 |
+
desc: null
|
612 |
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value: false
|
613 |
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gradient_checkpointing:
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614 |
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615 |
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|
616 |
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gradient_checkpointing_kwargs:
|
617 |
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desc: null
|
618 |
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|
619 |
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include_inputs_for_metrics:
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620 |
+
desc: null
|
621 |
+
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|
622 |
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fp16_backend:
|
623 |
+
desc: null
|
624 |
+
value: auto
|
625 |
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push_to_hub_model_id:
|
626 |
+
desc: null
|
627 |
+
value: null
|
628 |
+
push_to_hub_organization:
|
629 |
+
desc: null
|
630 |
+
value: null
|
631 |
+
push_to_hub_token:
|
632 |
+
desc: null
|
633 |
+
value: <PUSH_TO_HUB_TOKEN>
|
634 |
+
mp_parameters:
|
635 |
+
desc: null
|
636 |
+
value: ''
|
637 |
+
auto_find_batch_size:
|
638 |
+
desc: null
|
639 |
+
value: false
|
640 |
+
full_determinism:
|
641 |
+
desc: null
|
642 |
+
value: false
|
643 |
+
torchdynamo:
|
644 |
+
desc: null
|
645 |
+
value: null
|
646 |
+
ray_scope:
|
647 |
+
desc: null
|
648 |
+
value: last
|
649 |
+
ddp_timeout:
|
650 |
+
desc: null
|
651 |
+
value: 1800
|
652 |
+
torch_compile:
|
653 |
+
desc: null
|
654 |
+
value: false
|
655 |
+
torch_compile_backend:
|
656 |
+
desc: null
|
657 |
+
value: null
|
658 |
+
torch_compile_mode:
|
659 |
+
desc: null
|
660 |
+
value: null
|
661 |
+
dispatch_batches:
|
662 |
+
desc: null
|
663 |
+
value: null
|
664 |
+
split_batches:
|
665 |
+
desc: null
|
666 |
+
value: null
|
667 |
+
include_tokens_per_second:
|
668 |
+
desc: null
|
669 |
+
value: false
|
670 |
+
include_num_input_tokens_seen:
|
671 |
+
desc: null
|
672 |
+
value: false
|
673 |
+
neftune_noise_alpha:
|
674 |
+
desc: null
|
675 |
+
value: null
|
676 |
+
optim_target_modules:
|
677 |
+
desc: null
|
678 |
+
value: null
|
wandb/run-20240322_043407-hize5f4p/files/requirements.txt
ADDED
@@ -0,0 +1,510 @@
|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
1 |
+
Babel==2.14.0
|
2 |
+
CacheControl==0.14.0
|
3 |
+
Cython==3.0.9
|
4 |
+
Flask==2.2.5
|
5 |
+
GDAL==3.6.4
|
6 |
+
GitPython==3.1.42
|
7 |
+
Jinja2==3.1.3
|
8 |
+
Markdown==3.6
|
9 |
+
MarkupSafe==2.1.5
|
10 |
+
Pillow==9.4.0
|
11 |
+
PyDrive2==1.6.3
|
12 |
+
PyDrive==1.3.1
|
13 |
+
PyGObject==3.42.1
|
14 |
+
PyJWT==2.3.0
|
15 |
+
PyOpenGL==3.1.7
|
16 |
+
PySocks==1.7.1
|
17 |
+
PyWavelets==1.5.0
|
18 |
+
PyYAML==6.0.1
|
19 |
+
Pygments==2.16.1
|
20 |
+
SQLAlchemy==2.0.28
|
21 |
+
SecretStorage==3.3.1
|
22 |
+
Send2Trash==1.8.2
|
23 |
+
Sphinx==5.0.2
|
24 |
+
Werkzeug==3.0.1
|
25 |
+
absl-py==1.4.0
|
26 |
+
accelerate==0.28.0
|
27 |
+
aiohttp==3.9.3
|
28 |
+
aiosignal==1.3.1
|
29 |
+
alabaster==0.7.16
|
30 |
+
albumentations==1.3.1
|
31 |
+
altair==4.2.2
|
32 |
+
annotated-types==0.6.0
|
33 |
+
anyio==3.7.1
|
34 |
+
appdirs==1.4.4
|
35 |
+
argon2-cffi-bindings==21.2.0
|
36 |
+
argon2-cffi==23.1.0
|
37 |
+
array-record==0.5.0
|
38 |
+
arviz==0.15.1
|
39 |
+
astropy==5.3.4
|
40 |
+
astunparse==1.6.3
|
41 |
+
async-timeout==4.0.3
|
42 |
+
atpublic==4.0
|
43 |
+
attrs==23.2.0
|
44 |
+
audioread==3.0.1
|
45 |
+
autograd==1.6.2
|
46 |
+
backcall==0.2.0
|
47 |
+
beautifulsoup4==4.12.3
|
48 |
+
bidict==0.23.1
|
49 |
+
bigframes==0.25.0
|
50 |
+
bitsandbytes==0.43.0
|
51 |
+
bleach==6.1.0
|
52 |
+
blinker==1.4
|
53 |
+
blis==0.7.11
|
54 |
+
blosc2==2.0.0
|
55 |
+
bokeh==3.3.4
|
56 |
+
bqplot==0.12.43
|
57 |
+
branca==0.7.1
|
58 |
+
build==1.1.1
|
59 |
+
cachetools==5.3.3
|
60 |
+
catalogue==2.0.10
|
61 |
+
certifi==2024.2.2
|
62 |
+
cffi==1.16.0
|
63 |
+
chardet==5.2.0
|
64 |
+
charset-normalizer==3.3.2
|
65 |
+
chex==0.1.85
|
66 |
+
click-plugins==1.1.1
|
67 |
+
click==8.1.7
|
68 |
+
cligj==0.7.2
|
69 |
+
cloudpathlib==0.16.0
|
70 |
+
cloudpickle==2.2.1
|
71 |
+
cmake==3.27.9
|
72 |
+
cmdstanpy==1.2.1
|
73 |
+
colorcet==3.1.0
|
74 |
+
colorlover==0.3.0
|
75 |
+
colour==0.1.5
|
76 |
+
community==1.0.0b1
|
77 |
+
confection==0.1.4
|
78 |
+
cons==0.4.6
|
79 |
+
contextlib2==21.6.0
|
80 |
+
contourpy==1.2.0
|
81 |
+
cryptography==42.0.5
|
82 |
+
cufflinks==0.17.3
|
83 |
+
cupy-cuda12x==12.2.0
|
84 |
+
cvxopt==1.3.2
|
85 |
+
cvxpy==1.3.3
|
86 |
+
cycler==0.12.1
|
87 |
+
cymem==2.0.8
|
88 |
+
dask==2023.8.1
|
89 |
+
datascience==0.17.6
|
90 |
+
datasets==2.18.0
|
91 |
+
db-dtypes==1.2.0
|
92 |
+
dbus-python==1.2.18
|
93 |
+
debugpy==1.6.6
|
94 |
+
decorator==4.4.2
|
95 |
+
defusedxml==0.7.1
|
96 |
+
dill==0.3.8
|
97 |
+
distributed==2023.8.1
|
98 |
+
distro==1.7.0
|
99 |
+
dlib==19.24.2
|
100 |
+
dm-tree==0.1.8
|
101 |
+
docker-pycreds==0.4.0
|
102 |
+
docstring_parser==0.16
|
103 |
+
docutils==0.18.1
|
104 |
+
dopamine-rl==4.0.6
|
105 |
+
duckdb==0.9.2
|
106 |
+
earthengine-api==0.1.394
|
107 |
+
easydict==1.13
|
108 |
+
ecos==2.0.13
|
109 |
+
editdistance==0.6.2
|
110 |
+
eerepr==0.0.4
|
111 |
+
einops==0.7.0
|
112 |
+
en-core-web-sm==3.7.1
|
113 |
+
entrypoints==0.4
|
114 |
+
et-xmlfile==1.1.0
|
115 |
+
etils==1.7.0
|
116 |
+
etuples==0.3.9
|
117 |
+
exceptiongroup==1.2.0
|
118 |
+
fastai==2.7.14
|
119 |
+
fastcore==1.5.29
|
120 |
+
fastdownload==0.0.7
|
121 |
+
fastjsonschema==2.19.1
|
122 |
+
fastprogress==1.0.3
|
123 |
+
fastrlock==0.8.2
|
124 |
+
filelock==3.13.1
|
125 |
+
fiona==1.9.6
|
126 |
+
firebase-admin==5.3.0
|
127 |
+
flatbuffers==24.3.7
|
128 |
+
flax==0.8.2
|
129 |
+
folium==0.14.0
|
130 |
+
fonttools==4.49.0
|
131 |
+
frozendict==2.4.0
|
132 |
+
frozenlist==1.4.1
|
133 |
+
fsspec==2023.6.0
|
134 |
+
future==0.18.3
|
135 |
+
gast==0.5.4
|
136 |
+
gcsfs==2023.6.0
|
137 |
+
gdown==4.7.3
|
138 |
+
geemap==0.32.0
|
139 |
+
gensim==4.3.2
|
140 |
+
geocoder==1.38.1
|
141 |
+
geographiclib==2.0
|
142 |
+
geopandas==0.13.2
|
143 |
+
geopy==2.3.0
|
144 |
+
gin-config==0.5.0
|
145 |
+
gitdb==4.0.11
|
146 |
+
glob2==0.7
|
147 |
+
google-ai-generativelanguage==0.4.0
|
148 |
+
google-api-core==2.11.1
|
149 |
+
google-api-python-client==2.84.0
|
150 |
+
google-auth-httplib2==0.1.1
|
151 |
+
google-auth-oauthlib==1.2.0
|
152 |
+
google-auth==2.27.0
|
153 |
+
google-cloud-aiplatform==1.44.0
|
154 |
+
google-cloud-bigquery-connection==1.12.1
|
155 |
+
google-cloud-bigquery-storage==2.24.0
|
156 |
+
google-cloud-bigquery==3.12.0
|
157 |
+
google-cloud-core==2.3.3
|
158 |
+
google-cloud-datastore==2.15.2
|
159 |
+
google-cloud-firestore==2.11.1
|
160 |
+
google-cloud-functions==1.13.3
|
161 |
+
google-cloud-iam==2.14.3
|
162 |
+
google-cloud-language==2.13.3
|
163 |
+
google-cloud-resource-manager==1.12.3
|
164 |
+
google-cloud-storage==2.8.0
|
165 |
+
google-cloud-translate==3.11.3
|
166 |
+
google-colab==1.0.0
|
167 |
+
google-crc32c==1.5.0
|
168 |
+
google-generativeai==0.3.2
|
169 |
+
google-pasta==0.2.0
|
170 |
+
google-resumable-media==2.7.0
|
171 |
+
google==2.0.3
|
172 |
+
googleapis-common-protos==1.63.0
|
173 |
+
googledrivedownloader==0.4
|
174 |
+
graphviz==0.20.1
|
175 |
+
greenlet==3.0.3
|
176 |
+
grpc-google-iam-v1==0.13.0
|
177 |
+
grpcio-status==1.48.2
|
178 |
+
grpcio==1.62.1
|
179 |
+
gspread-dataframe==3.3.1
|
180 |
+
gspread==3.4.2
|
181 |
+
gym-notices==0.0.8
|
182 |
+
gym==0.25.2
|
183 |
+
h5netcdf==1.3.0
|
184 |
+
h5py==3.9.0
|
185 |
+
holidays==0.44
|
186 |
+
holoviews==1.17.1
|
187 |
+
html5lib==1.1
|
188 |
+
httpimport==1.3.1
|
189 |
+
httplib2==0.22.0
|
190 |
+
huggingface-hub==0.20.3
|
191 |
+
humanize==4.7.0
|
192 |
+
hyperopt==0.2.7
|
193 |
+
ibis-framework==8.0.0
|
194 |
+
idna==3.6
|
195 |
+
imageio-ffmpeg==0.4.9
|
196 |
+
imageio==2.31.6
|
197 |
+
imagesize==1.4.1
|
198 |
+
imbalanced-learn==0.10.1
|
199 |
+
imgaug==0.4.0
|
200 |
+
importlib_metadata==7.0.2
|
201 |
+
importlib_resources==6.3.0
|
202 |
+
imutils==0.5.4
|
203 |
+
inflect==7.0.0
|
204 |
+
iniconfig==2.0.0
|
205 |
+
intel-openmp==2023.2.4
|
206 |
+
ipyevents==2.0.2
|
207 |
+
ipyfilechooser==0.6.0
|
208 |
+
ipykernel==5.5.6
|
209 |
+
ipyleaflet==0.18.2
|
210 |
+
ipython-genutils==0.2.0
|
211 |
+
ipython-sql==0.5.0
|
212 |
+
ipython==7.34.0
|
213 |
+
ipytree==0.2.2
|
214 |
+
ipywidgets==7.7.1
|
215 |
+
itsdangerous==2.1.2
|
216 |
+
jax==0.4.23
|
217 |
+
jaxlib==0.4.23+cuda12.cudnn89
|
218 |
+
jeepney==0.7.1
|
219 |
+
jieba==0.42.1
|
220 |
+
joblib==1.3.2
|
221 |
+
jsonpickle==3.0.3
|
222 |
+
jsonschema-specifications==2023.12.1
|
223 |
+
jsonschema==4.19.2
|
224 |
+
jupyter-client==6.1.12
|
225 |
+
jupyter-console==6.1.0
|
226 |
+
jupyter-server==1.24.0
|
227 |
+
jupyter_core==5.7.2
|
228 |
+
jupyterlab_pygments==0.3.0
|
229 |
+
jupyterlab_widgets==3.0.10
|
230 |
+
kaggle==1.5.16
|
231 |
+
kagglehub==0.2.0
|
232 |
+
keras==2.15.0
|
233 |
+
keyring==23.5.0
|
234 |
+
kiwisolver==1.4.5
|
235 |
+
langcodes==3.3.0
|
236 |
+
launchpadlib==1.10.16
|
237 |
+
lazr.restfulclient==0.14.4
|
238 |
+
lazr.uri==1.0.6
|
239 |
+
lazy_loader==0.3
|
240 |
+
libclang==16.0.6
|
241 |
+
librosa==0.10.1
|
242 |
+
lightgbm==4.1.0
|
243 |
+
linkify-it-py==2.0.3
|
244 |
+
llvmlite==0.41.1
|
245 |
+
locket==1.0.0
|
246 |
+
logical-unification==0.4.6
|
247 |
+
lxml==4.9.4
|
248 |
+
malloy==2023.1067
|
249 |
+
markdown-it-py==3.0.0
|
250 |
+
matplotlib-inline==0.1.6
|
251 |
+
matplotlib-venn==0.11.10
|
252 |
+
matplotlib==3.7.1
|
253 |
+
mdit-py-plugins==0.4.0
|
254 |
+
mdurl==0.1.2
|
255 |
+
miniKanren==1.0.3
|
256 |
+
missingno==0.5.2
|
257 |
+
mistune==0.8.4
|
258 |
+
mizani==0.9.3
|
259 |
+
mkl==2023.2.0
|
260 |
+
ml-dtypes==0.2.0
|
261 |
+
mlxtend==0.22.0
|
262 |
+
more-itertools==10.1.0
|
263 |
+
moviepy==1.0.3
|
264 |
+
mpmath==1.3.0
|
265 |
+
msgpack==1.0.8
|
266 |
+
multidict==6.0.5
|
267 |
+
multipledispatch==1.0.0
|
268 |
+
multiprocess==0.70.16
|
269 |
+
multitasking==0.0.11
|
270 |
+
murmurhash==1.0.10
|
271 |
+
music21==9.1.0
|
272 |
+
natsort==8.4.0
|
273 |
+
nbclassic==1.0.0
|
274 |
+
nbclient==0.10.0
|
275 |
+
nbconvert==6.5.4
|
276 |
+
nbformat==5.10.2
|
277 |
+
nest-asyncio==1.6.0
|
278 |
+
networkx==3.2.1
|
279 |
+
nibabel==4.0.2
|
280 |
+
nltk==3.8.1
|
281 |
+
notebook==6.5.5
|
282 |
+
notebook_shim==0.2.4
|
283 |
+
numba==0.58.1
|
284 |
+
numexpr==2.9.0
|
285 |
+
numpy==1.25.2
|
286 |
+
nvidia-cublas-cu12==12.1.3.1
|
287 |
+
nvidia-cuda-cupti-cu12==12.1.105
|
288 |
+
nvidia-cuda-nvrtc-cu12==12.1.105
|
289 |
+
nvidia-cuda-runtime-cu12==12.1.105
|
290 |
+
nvidia-cudnn-cu12==8.9.2.26
|
291 |
+
nvidia-cufft-cu12==11.0.2.54
|
292 |
+
nvidia-curand-cu12==10.3.2.106
|
293 |
+
nvidia-cusolver-cu12==11.4.5.107
|
294 |
+
nvidia-cusparse-cu12==12.1.0.106
|
295 |
+
nvidia-nccl-cu12==2.19.3
|
296 |
+
nvidia-nvjitlink-cu12==12.4.99
|
297 |
+
nvidia-nvtx-cu12==12.1.105
|
298 |
+
oauth2client==4.1.3
|
299 |
+
oauthlib==3.2.2
|
300 |
+
opencv-contrib-python==4.8.0.76
|
301 |
+
opencv-python-headless==4.9.0.80
|
302 |
+
opencv-python==4.8.0.76
|
303 |
+
openpyxl==3.1.2
|
304 |
+
opt-einsum==3.3.0
|
305 |
+
optax==0.2.1
|
306 |
+
orbax-checkpoint==0.4.4
|
307 |
+
osqp==0.6.2.post8
|
308 |
+
packaging==24.0
|
309 |
+
pandas-datareader==0.10.0
|
310 |
+
pandas-gbq==0.19.2
|
311 |
+
pandas-stubs==1.5.3.230304
|
312 |
+
pandas==1.5.3
|
313 |
+
pandocfilters==1.5.1
|
314 |
+
panel==1.3.8
|
315 |
+
param==2.0.2
|
316 |
+
parso==0.8.3
|
317 |
+
parsy==2.1
|
318 |
+
partd==1.4.1
|
319 |
+
pathlib==1.0.1
|
320 |
+
patsy==0.5.6
|
321 |
+
peewee==3.17.1
|
322 |
+
peft==0.10.1.dev0
|
323 |
+
pexpect==4.9.0
|
324 |
+
pickleshare==0.7.5
|
325 |
+
pip-tools==6.13.0
|
326 |
+
pip==23.1.2
|
327 |
+
platformdirs==4.2.0
|
328 |
+
plotly==5.15.0
|
329 |
+
plotnine==0.12.4
|
330 |
+
pluggy==1.4.0
|
331 |
+
polars==0.20.2
|
332 |
+
pooch==1.8.1
|
333 |
+
portpicker==1.5.2
|
334 |
+
prefetch-generator==1.0.3
|
335 |
+
preshed==3.0.9
|
336 |
+
prettytable==3.10.0
|
337 |
+
proglog==0.1.10
|
338 |
+
progressbar2==4.2.0
|
339 |
+
prometheus_client==0.20.0
|
340 |
+
promise==2.3
|
341 |
+
prompt-toolkit==3.0.43
|
342 |
+
prophet==1.1.5
|
343 |
+
proto-plus==1.23.0
|
344 |
+
protobuf==3.20.3
|
345 |
+
psutil==5.9.5
|
346 |
+
psycopg2==2.9.9
|
347 |
+
ptyprocess==0.7.0
|
348 |
+
py-cpuinfo==9.0.0
|
349 |
+
py4j==0.10.9.7
|
350 |
+
pyOpenSSL==24.1.0
|
351 |
+
pyarrow-hotfix==0.6
|
352 |
+
pyarrow==14.0.2
|
353 |
+
pyasn1-modules==0.3.0
|
354 |
+
pyasn1==0.5.1
|
355 |
+
pycocotools==2.0.7
|
356 |
+
pycparser==2.21
|
357 |
+
pydantic==2.6.4
|
358 |
+
pydantic_core==2.16.3
|
359 |
+
pydata-google-auth==1.8.2
|
360 |
+
pydot-ng==2.0.0
|
361 |
+
pydot==1.4.2
|
362 |
+
pydotplus==2.0.2
|
363 |
+
pyerfa==2.0.1.1
|
364 |
+
pygame==2.5.2
|
365 |
+
pymc==5.10.4
|
366 |
+
pymystem3==0.2.0
|
367 |
+
pyparsing==3.1.2
|
368 |
+
pyperclip==1.8.2
|
369 |
+
pyproj==3.6.1
|
370 |
+
pyproject_hooks==1.0.0
|
371 |
+
pyshp==2.3.1
|
372 |
+
pytensor==2.18.6
|
373 |
+
pytest==7.4.4
|
374 |
+
python-apt==0.0.0
|
375 |
+
python-box==7.1.1
|
376 |
+
python-dateutil==2.8.2
|
377 |
+
python-louvain==0.16
|
378 |
+
python-slugify==8.0.4
|
379 |
+
python-utils==3.8.2
|
380 |
+
pytz==2023.4
|
381 |
+
pyviz_comms==3.0.1
|
382 |
+
pyzmq==23.2.1
|
383 |
+
qdldl==0.1.7.post0
|
384 |
+
qudida==0.0.4
|
385 |
+
ratelim==0.1.6
|
386 |
+
referencing==0.33.0
|
387 |
+
regex==2023.12.25
|
388 |
+
requests-oauthlib==1.4.0
|
389 |
+
requests==2.31.0
|
390 |
+
requirements-parser==0.5.0
|
391 |
+
rich==13.7.1
|
392 |
+
rpds-py==0.18.0
|
393 |
+
rpy2==3.4.2
|
394 |
+
rsa==4.9
|
395 |
+
safetensors==0.4.2
|
396 |
+
scikit-image==0.19.3
|
397 |
+
scikit-learn==1.2.2
|
398 |
+
scipy==1.11.4
|
399 |
+
scooby==0.9.2
|
400 |
+
scs==3.2.4.post1
|
401 |
+
seaborn==0.13.1
|
402 |
+
sentencepiece==0.1.99
|
403 |
+
sentry-sdk==1.43.0
|
404 |
+
setproctitle==1.3.3
|
405 |
+
setuptools==67.7.2
|
406 |
+
shapely==2.0.3
|
407 |
+
shtab==1.7.1
|
408 |
+
six==1.16.0
|
409 |
+
six==1.16.0
|
410 |
+
sklearn-pandas==2.2.0
|
411 |
+
smart-open==6.4.0
|
412 |
+
smmap==5.0.1
|
413 |
+
sniffio==1.3.1
|
414 |
+
snowballstemmer==2.2.0
|
415 |
+
sortedcontainers==2.4.0
|
416 |
+
soundfile==0.12.1
|
417 |
+
soupsieve==2.5
|
418 |
+
soxr==0.3.7
|
419 |
+
spacy-legacy==3.0.12
|
420 |
+
spacy-loggers==1.0.5
|
421 |
+
spacy==3.7.4
|
422 |
+
sphinxcontrib-applehelp==1.0.8
|
423 |
+
sphinxcontrib-devhelp==1.0.6
|
424 |
+
sphinxcontrib-htmlhelp==2.0.5
|
425 |
+
sphinxcontrib-jsmath==1.0.1
|
426 |
+
sphinxcontrib-qthelp==1.0.7
|
427 |
+
sphinxcontrib-serializinghtml==1.1.10
|
428 |
+
sqlglot==20.11.0
|
429 |
+
sqlparse==0.4.4
|
430 |
+
srsly==2.4.8
|
431 |
+
stanio==0.3.0
|
432 |
+
statsmodels==0.14.1
|
433 |
+
sympy==1.12
|
434 |
+
tables==3.8.0
|
435 |
+
tabulate==0.9.0
|
436 |
+
tbb==2021.11.0
|
437 |
+
tblib==3.0.0
|
438 |
+
tenacity==8.2.3
|
439 |
+
tensorboard-data-server==0.7.2
|
440 |
+
tensorboard==2.15.2
|
441 |
+
tensorflow-datasets==4.9.4
|
442 |
+
tensorflow-estimator==2.15.0
|
443 |
+
tensorflow-gcs-config==2.15.0
|
444 |
+
tensorflow-hub==0.16.1
|
445 |
+
tensorflow-io-gcs-filesystem==0.36.0
|
446 |
+
tensorflow-metadata==1.14.0
|
447 |
+
tensorflow-probability==0.23.0
|
448 |
+
tensorflow==2.15.0
|
449 |
+
tensorstore==0.1.45
|
450 |
+
termcolor==2.4.0
|
451 |
+
terminado==0.18.1
|
452 |
+
text-unidecode==1.3
|
453 |
+
textblob==0.17.1
|
454 |
+
tf-slim==1.1.0
|
455 |
+
tf_keras==2.15.1
|
456 |
+
thinc==8.2.3
|
457 |
+
threadpoolctl==3.3.0
|
458 |
+
tifffile==2024.2.12
|
459 |
+
tinycss2==1.2.1
|
460 |
+
tokenizers==0.15.2
|
461 |
+
toml==0.10.2
|
462 |
+
tomli==2.0.1
|
463 |
+
toolz==0.12.1
|
464 |
+
torch==2.2.1+cu121
|
465 |
+
torchaudio==2.2.1+cu121
|
466 |
+
torchdata==0.7.1
|
467 |
+
torchsummary==1.5.1
|
468 |
+
torchtext==0.17.1
|
469 |
+
torchvision==0.17.1+cu121
|
470 |
+
tornado==6.3.3
|
471 |
+
tqdm==4.66.2
|
472 |
+
traitlets==5.7.1
|
473 |
+
traittypes==0.2.1
|
474 |
+
transformers==4.39.0
|
475 |
+
triton==2.2.0
|
476 |
+
trl==0.8.1
|
477 |
+
tweepy==4.14.0
|
478 |
+
typer==0.9.0
|
479 |
+
types-pytz==2024.1.0.20240203
|
480 |
+
types-setuptools==69.2.0.20240317
|
481 |
+
typing_extensions==4.10.0
|
482 |
+
tyro==0.7.3
|
483 |
+
tzlocal==5.2
|
484 |
+
uc-micro-py==1.0.3
|
485 |
+
uritemplate==4.1.1
|
486 |
+
urllib3==2.0.7
|
487 |
+
vega-datasets==0.9.0
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wandb/run-20240322_043407-hize5f4p/files/wandb-summary.json
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