| --- |
| base_model: mistralai/Mistral-Nemo-Instruct-2407 |
| library_name: peft |
| license: other |
| tags: |
| - llama-factory |
| - lora |
| - generated_from_trainer |
| model-index: |
| - name: epidemiology_sft_10000_mcq_2epoch |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # epidemiology_sft_10000_mcq_2epoch |
|
|
| This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the epidemiology_10000_mcq dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0020 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 10 |
| - eval_batch_size: 10 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - total_train_batch_size: 40 |
| - total_eval_batch_size: 40 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - num_epochs: 2 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.0042 | 0.1333 | 30 | 0.0041 | |
| | 0.0039 | 0.2667 | 60 | 0.0039 | |
| | 0.0039 | 0.4 | 90 | 0.0039 | |
| | 0.0039 | 0.5333 | 120 | 0.0039 | |
| | 0.0033 | 0.6667 | 150 | 0.0031 | |
| | 0.0029 | 0.8 | 180 | 0.0029 | |
| | 0.0028 | 0.9333 | 210 | 0.0025 | |
| | 0.0025 | 1.0667 | 240 | 0.0024 | |
| | 0.0024 | 1.2 | 270 | 0.0024 | |
| | 0.0027 | 1.3333 | 300 | 0.0024 | |
| | 0.0025 | 1.4667 | 330 | 0.0023 | |
| | 0.0023 | 1.6 | 360 | 0.0022 | |
| | 0.0023 | 1.7333 | 390 | 0.0021 | |
| | 0.002 | 1.8667 | 420 | 0.0020 | |
| | 0.0022 | 2.0 | 450 | 0.0020 | |
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| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.46.0 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.20.1 |
