| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/electra-small-discriminator |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: electra-small-touche-base-binary |
| 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. --> |
|
|
| # electra-small-touche-base-binary |
|
|
| This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6289 |
| - Accuracy: 0.665 |
| - Macro F1: 0.6649 |
| - Fallacy F1: 0.6700 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 3e-05 |
| - train_batch_size: 16 |
| - 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 | Macro F1 | Fallacy F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:----------:| |
| | 0.6951 | 1.0 | 47 | 0.6898 | 0.555 | 0.5094 | 0.3597 | |
| | 0.6876 | 2.0 | 94 | 0.6786 | 0.64 | 0.64 | 0.64 | |
| | 0.6429 | 3.0 | 141 | 0.6572 | 0.63 | 0.6161 | 0.5432 | |
| | 0.6258 | 4.0 | 188 | 0.6353 | 0.645 | 0.6430 | 0.6698 | |
| | 0.5856 | 5.0 | 235 | 0.6289 | 0.665 | 0.6649 | 0.6700 | |
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|
| ### Framework versions |
|
|
| - Transformers 5.9.0 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
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|
