| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - accuracy |
| model-index: |
| - name: modernbert-tr-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. --> |
|
|
| # modernbert-tr-classifier |
|
|
| This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7290 |
| - F1: 0.8554 |
| - Accuracy: 0.8537 |
|
|
| ## 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: 8e-05 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 256 |
| - optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
| | 3.704 | 1.0 | 19 | 1.4201 | 0.4022 | 0.4553 | |
| | 2.3894 | 2.0 | 38 | 0.9204 | 0.6456 | 0.6423 | |
| | 1.4461 | 3.0 | 57 | 0.5806 | 0.8250 | 0.8211 | |
| | 0.9515 | 4.0 | 76 | 0.4542 | 0.8714 | 0.8699 | |
| | 0.585 | 5.0 | 95 | 0.4316 | 0.8862 | 0.8862 | |
| | 0.3665 | 6.0 | 114 | 0.5989 | 0.8533 | 0.8537 | |
| | 0.1882 | 7.0 | 133 | 0.7290 | 0.8554 | 0.8537 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.0 |
| - Pytorch 2.5.1+cu118 |
| - Datasets 3.1.0 |
| - Tokenizers 0.21.0 |
| |
