| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/muril-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: results |
| 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3232 |
| - Accuracy: 0.8957 |
| - F1: 0.8913 |
| - Precision: 0.8856 |
| - Recall: 0.8970 |
|
|
| ## 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 |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.4738 | 1.0 | 275 | 0.4001 | 0.8793 | 0.8768 | 0.8537 | 0.9013 | |
| | 0.3356 | 2.0 | 550 | 0.3046 | 0.9039 | 0.8967 | 0.9189 | 0.8755 | |
| | 0.2047 | 3.0 | 825 | 0.3029 | 0.9059 | 0.9013 | 0.9013 | 0.9013 | |
| | 0.2142 | 4.0 | 1100 | 0.3232 | 0.8957 | 0.8913 | 0.8856 | 0.8970 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
