| library_name: transformers | |
| license: apache-2.0 | |
| base_model: distilbert-base-cased | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: outputs | |
| 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 | |
| This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0122 | |
| - F1 Micro: 0.6194 | |
| - F1 Macro: 0.0119 | |
| - Precision Micro: 0.7934 | |
| - Recall Micro: 0.5080 | |
| - Subset Accuracy: 0.3677 | |
| ## 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: 32 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - 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: 1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Precision Micro | Recall Micro | Subset Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:---------------:| | |
| | 0.0129 | 1.0 | 1025 | 0.0122 | 0.6194 | 0.0119 | 0.7934 | 0.5080 | 0.3677 | | |
| ### Framework versions | |
| - Transformers 4.50.3 | |
| - Pytorch 2.6.0+cu124 | |
| - Tokenizers 0.21.1 | |