Commit
•
0b8df04
1
Parent(s):
ae7e378
End of training
Browse files- README.md +59 -0
- adapter_config.json +28 -0
- adapter_model.bin +3 -0
- adapter_model.safetensors +3 -0
- all_results.json +7 -0
- args.txt +11 -0
- train_results.json +7 -0
- trainer_state.json +936 -0
- training_args.bin +3 -0
README.md
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---
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license: llama2
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base_model: lmsys/vicuna-7b-v1.5
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tags:
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- generated_from_trainer
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model-index:
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- name: finetune_arc_1_cot
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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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# finetune_arc_1_cot
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This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2197
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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: 0.0001
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 5
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.2522 | 1.0 | 150 | 1.2197 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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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": "lmsys/vicuna-7b-v1.5",
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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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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 64,
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"lora_dropout": 0.1,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"q_proj",
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"up_proj",
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"v_proj",
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"down_proj",
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"o_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:71abeb44c21cccca9e876254bdf78370d1962ba40687714d22f6f9c68ebc368e
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size 160069834
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:36cf62dc07145e503a951e36bb6e6fa1e29a0d36300ee074c22a997c77c6eb7f
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size 159967880
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all_results.json
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{
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"epoch": 1.0,
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"train_loss": 1.2855440950393677,
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"train_runtime": 278.1355,
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"train_samples_per_second": 2.157,
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"train_steps_per_second": 0.539
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}
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args.txt
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base_model_name: lmsys/vicuna-7b-v1.5
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batch_size: 4
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cot: true
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dataset_name: BENBENBENb/ARC1000COT
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epochs: 1
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eval_strategy: epoch
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learning_rate: 0.0001
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logging_steps: 1
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output_dir: BENBENBENb/finetune_arc_1_cot
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seed: 42
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warmup_steps: 5
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train_results.json
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{
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"epoch": 1.0,
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"train_loss": 1.2855440950393677,
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"train_runtime": 278.1355,
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"train_samples_per_second": 2.157,
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"train_steps_per_second": 0.539
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}
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trainer_state.json
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