| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| 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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.3402 |
| - Accuracy: 0.8646 |
| - F1: 0.8427 |
| - Precision: 0.8436 |
| - Recall: 0.8445 |
|
|
| ## 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 |
| - lr_scheduler_warmup_steps: 200 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 2.4083 | 1.0 | 570 | 1.4497 | 0.7934 | 0.7845 | 0.7743 | 0.8101 | |
| | 1.3497 | 2.0 | 1140 | 1.3323 | 0.8307 | 0.8161 | 0.8101 | 0.8312 | |
| | 1.2217 | 3.0 | 1710 | 1.3071 | 0.8544 | 0.8341 | 0.8334 | 0.8380 | |
| | 1.1486 | 4.0 | 2280 | 1.2961 | 0.8539 | 0.8389 | 0.8394 | 0.8430 | |
| | 1.0651 | 5.0 | 2850 | 1.2995 | 0.8618 | 0.8428 | 0.8417 | 0.8470 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
