| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased-classifier |
| 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. --> |
|
|
| # distilbert-base-uncased-classifier |
|
|
| This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2505 |
| - Accuracy: 0.8919 |
| - F1: 0.7899 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - 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: linear |
| - num_epochs: 2 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | No log | 0 | 0 | 0.6737 | 0.7493 | 0.0440 | |
| | No log | 0.2020 | 79 | 0.3465 | 0.8602 | 0.6820 | |
| | No log | 0.4041 | 158 | 0.3404 | 0.8458 | 0.7371 | |
| | No log | 0.6061 | 237 | 0.2951 | 0.8761 | 0.7650 | |
| | No log | 0.8082 | 316 | 0.2763 | 0.8862 | 0.7893 | |
| | No log | 1.0102 | 395 | 0.2732 | 0.8818 | 0.7747 | |
| | No log | 1.2123 | 474 | 0.2707 | 0.8905 | 0.7865 | |
| | 0.3426 | 1.4143 | 553 | 0.2516 | 0.8963 | 0.7989 | |
| | 0.3426 | 1.6164 | 632 | 0.2434 | 0.8963 | 0.7943 | |
| | 0.3426 | 1.8184 | 711 | 0.2505 | 0.8919 | 0.7899 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.51.3 |
| - Pytorch 2.7.0+cu126 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
|
|
