| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| pipeline_tag: text-classification |
| model-index: |
| - name: fator-argument-quality |
| 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. --> |
|
|
| # fator-argument-quality |
|
|
| 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: 0.5797 |
| - Accuracy: 0.8014 |
| - F1 Macro: 0.5806 |
| - F1 Weighted: 0.7459 |
|
|
| ## 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: 64 |
| - 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: 0.1 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.5548 | 1.0 | 558 | 0.5412 | 0.7741 | 0.3669 | 0.7188 | |
| | 0.4892 | 2.0 | 1116 | 0.5830 | 0.7866 | 0.3644 | 0.7055 | |
| | 0.4455 | 3.0 | 1674 | 0.5797 | 0.7814 | 0.4606 | 0.7449 | |
| | 0.3561 | 4.0 | 2232 | 0.6330 | 0.7902 | 0.4996 | 0.7457 | |
| | 0.3084 | 5.0 | 2790 | 0.6744 | 0.8057 | 0.5806 | 0.7459 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
