| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: results |
| 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2719 |
| - Accuracy: 0.9166 |
| - Precision: 0.8914 |
| - Recall: 0.9496 |
| - F1: 0.9195 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - 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: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.2355 | 1.0 | 2232 | 0.2344 | 0.9072 | 0.9319 | 0.8795 | 0.9049 | |
| | 0.1550 | 2.0 | 4464 | 0.2906 | 0.9100 | 0.8825 | 0.9468 | 0.9135 | |
| | 0.0939 | 3.0 | 6696 | 0.3709 | 0.9115 | 0.9031 | 0.9227 | 0.9128 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.14.1 |
| - Pytorch 2.14.0.dev20260725+cu130 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
