Upload folder using huggingface_hub
Browse files- README.md +129 -0
- adapter_config.json +32 -0
- adapter_model.bin +3 -0
- checkpoint-20/README.md +204 -0
- checkpoint-20/adapter_config.json +32 -0
- checkpoint-20/adapter_model.safetensors +3 -0
- checkpoint-20/optimizer.pt +3 -0
- checkpoint-20/rng_state.pth +3 -0
- checkpoint-20/scheduler.pt +3 -0
- checkpoint-20/trainer_state.json +149 -0
- checkpoint-20/training_args.bin +3 -0
- config.json +40 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +44 -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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- 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: med_Mistral
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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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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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adapter: qlora
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base_model: mistralai/Mistral-7B-v0.1
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bf16: false
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dataset_prepared_path: null
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datasets:
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- path: joseagmz/MedQnA_version3
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type: context_qa.load_v2
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debug: null
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deepspeed: null
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early_stopping_patience: null
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evals_per_epoch: null
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flash_attention: false
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fp16: true
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps: 1
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gradient_checkpointing: true
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group_by_length: false
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is_llama_derived_model: true
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learning_rate: 0.0002
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load_in_4bit: true
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load_in_8bit: false
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local_rank: null
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logging_steps: 1
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lora_alpha: 16
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lora_dropout: 0.05
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lora_fan_in_fan_out: null
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lora_model_dir: null
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lora_r: 32
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lora_target_linear: true
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lora_target_modules: null
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lr_scheduler: cosine
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max_steps: 20
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micro_batch_size: 1
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mlflow_experiment_name: colab-example
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model_type: MistralForCausalLM
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num_epochs: 4
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optimizer: paged_adamw_32bit
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output_dir: ./med_Mistral
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pad_to_sequence_len: true
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resume_from_checkpoint: null
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sample_packing: true
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saves_per_epoch: null
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sequence_len: 1096
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special_tokens: null
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strict: false
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tf32: false
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tokenizer_type: LlamaTokenizer
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train_on_inputs: false
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val_set_size: 0.05
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wandb_entity: null
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wandb_log_model: null
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wandb_name: null
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wandb_project: null
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wandb_watch: null
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warmup_steps: 10
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weight_decay: 0.0
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xformers_attention: null
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```
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</details><br>
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# med_Mistral
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3152
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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: 1
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- eval_batch_size: 1
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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: cosine
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- lr_scheduler_warmup_steps: 10
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- training_steps: 20
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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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| 1.9831 | 0.0 | 20 | 1.3152 |
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### Framework versions
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- PEFT 0.8.2
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- Transformers 4.38.0.dev0
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- Pytorch 2.1.2+cu121
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- Datasets 2.17.0
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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": "mistralai/Mistral-7B-v0.1",
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"bias": "none",
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"fan_in_fan_out": null,
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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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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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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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"o_proj",
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"down_proj",
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"up_proj",
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"k_proj",
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"gate_proj",
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"v_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_rslora": false
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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 sha256:9ded548455d523e046fefbb08206e6ed0c11e265e6cadf16f28af2989ec48912
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size 335706186
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checkpoint-20/README.md
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---
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library_name: peft
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base_model: mistralai/Mistral-7B-v0.1
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
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|
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- **Hardware Type:** [More Information Needed]
|
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+
- **Hours used:** [More Information Needed]
|
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+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
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+
|
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+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
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+
[More Information Needed]
|
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+
|
163 |
+
#### Hardware
|
164 |
+
|
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+
[More Information Needed]
|
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+
|
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+
#### Software
|
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+
|
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+
[More Information Needed]
|
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+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
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+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
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+
|
187 |
+
[More Information Needed]
|
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+
|
189 |
+
## More Information [optional]
|
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+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
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+
|
201 |
+
|
202 |
+
### Framework versions
|
203 |
+
|
204 |
+
- PEFT 0.8.2
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1 |
+
{
|
2 |
+
"add_bos_token": true,
|
3 |
+
"add_eos_token": false,
|
4 |
+
"added_tokens_decoder": {
|
5 |
+
"0": {
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6 |
+
"content": "<unk>",
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7 |
+
"lstrip": false,
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8 |
+
"normalized": false,
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9 |
+
"rstrip": false,
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10 |
+
"single_word": false,
|
11 |
+
"special": true
|
12 |
+
},
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13 |
+
"1": {
|
14 |
+
"content": "<s>",
|
15 |
+
"lstrip": false,
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16 |
+
"normalized": false,
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17 |
+
"rstrip": false,
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18 |
+
"single_word": false,
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19 |
+
"special": true
|
20 |
+
},
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21 |
+
"2": {
|
22 |
+
"content": "</s>",
|
23 |
+
"lstrip": false,
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24 |
+
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
+
"single_word": false,
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27 |
+
"special": true
|
28 |
+
}
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29 |
+
},
|
30 |
+
"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"clean_up_tokenization_spaces": false,
|
33 |
+
"eos_token": "</s>",
|
34 |
+
"legacy": true,
|
35 |
+
"model_max_length": 1000000000000000019884624838656,
|
36 |
+
"pad_token": "</s>",
|
37 |
+
"sp_model_kwargs": {},
|
38 |
+
"spaces_between_special_tokens": false,
|
39 |
+
"tokenizer_class": "LlamaTokenizer",
|
40 |
+
"trust_remote_code": false,
|
41 |
+
"unk_token": "<unk>",
|
42 |
+
"use_default_system_prompt": false,
|
43 |
+
"use_fast": true
|
44 |
+
}
|