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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: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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model-index: |
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- name: lora_test |
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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: lora |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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bf16: auto |
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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: 4 |
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flash_attention: true |
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fp16: null |
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fsdp: null |
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fsdp_config: null |
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gradient_accumulation_steps: 4 |
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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: false |
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load_in_8bit: true |
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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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lr_scheduler: cosine |
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micro_batch_size: 2 |
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model_type: LlamaForCausalLM |
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num_epochs: 4 |
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optimizer: adamw_bnb_8bit |
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output_dir: ./lora_test |
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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: 1 |
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sequence_len: 4096 |
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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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# lora_test |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7337 |
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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: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.6541 | 0.01 | 1 | 1.7634 | |
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| 1.2512 | 0.25 | 42 | 0.8978 | |
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| 1.1008 | 0.5 | 84 | 0.8307 | |
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| 1.0685 | 0.75 | 126 | 0.8026 | |
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| 1.1573 | 1.0 | 168 | 0.7850 | |
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| 0.9346 | 1.24 | 210 | 0.7729 | |
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| 1.0299 | 1.49 | 252 | 0.7612 | |
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| 1.0057 | 1.74 | 294 | 0.7544 | |
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| 0.976 | 1.99 | 336 | 0.7478 | |
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| 1.0765 | 2.22 | 378 | 0.7439 | |
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| 0.8845 | 2.47 | 420 | 0.7409 | |
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| 1.0198 | 2.73 | 462 | 0.7379 | |
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| 0.9712 | 2.98 | 504 | 0.7352 | |
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| 0.9069 | 3.21 | 546 | 0.7350 | |
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| 0.8973 | 3.46 | 588 | 0.7342 | |
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| 0.9359 | 3.71 | 630 | 0.7337 | |
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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 2.17.1 |
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- Tokenizers 0.15.0 |
