| --- |
| base_model: StanfordAIMI/RadPhi-2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: outputs_20240325 |
| 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. --> |
|
|
| # outputs_20240325 |
| |
| This model is a fine-tuned version of [StanfordAIMI/RadPhi-2](https://huggingface.co/StanfordAIMI/RadPhi-2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0816 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 8 |
| - gradient_accumulation_steps: 32 |
| - total_train_batch_size: 2048 |
| - total_eval_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.05 |
| - num_epochs: 12.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.1831 | 0.64 | 25 | 0.1257 | |
| | 0.1239 | 1.28 | 50 | 0.1044 | |
| | 0.108 | 1.92 | 75 | 0.0995 | |
| | 0.0976 | 2.56 | 100 | 0.0978 | |
| | 0.094 | 3.2 | 125 | 0.0886 | |
| | 0.0828 | 3.84 | 150 | 0.0893 | |
| | 0.078 | 4.48 | 175 | 0.0907 | |
| | 0.0767 | 5.12 | 200 | 0.0866 | |
| | 0.0697 | 5.76 | 225 | 0.0840 | |
| | 0.0646 | 6.39 | 250 | 0.0819 | |
| | 0.0594 | 7.03 | 275 | 0.0795 | |
| | 0.052 | 7.67 | 300 | 0.0795 | |
| | 0.0478 | 8.31 | 325 | 0.0803 | |
| | 0.0447 | 8.95 | 350 | 0.0786 | |
| | 0.0392 | 9.59 | 375 | 0.0800 | |
| | 0.038 | 10.23 | 400 | 0.0813 | |
| | 0.0357 | 10.87 | 425 | 0.0810 | |
| | 0.035 | 11.51 | 450 | 0.0816 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.38.1 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
