| --- |
| library_name: transformers |
| license: mit |
| base_model: facebook/esm2_t12_35M_UR50D |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: checkpoints |
| 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. --> |
|
|
| # checkpoints |
|
|
| This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6773 |
| - Accuracy: 0.7253 |
| - Precision: 0.3633 |
| - Recall: 0.4923 |
| - F1: 0.4180 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.6281 | 1.0 | 1028 | 0.6312 | 0.7622 | 0.4035 | 0.3903 | 0.3968 | |
| | 0.5836 | 2.0 | 2056 | 0.6297 | 0.7553 | 0.3973 | 0.4273 | 0.4118 | |
| | 0.5832 | 3.0 | 3084 | 0.6605 | 0.7754 | 0.4326 | 0.3880 | 0.4091 | |
| | 0.5177 | 4.0 | 4112 | 0.6891 | 0.7604 | 0.4052 | 0.4179 | 0.4114 | |
| | 0.5016 | 5.0 | 5140 | 0.6773 | 0.7253 | 0.3633 | 0.4923 | 0.4180 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.13.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
