| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/muril-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: muril-ner-multilingual-v2 |
| 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. --> |
|
|
| # muril-ner-multilingual-v2 |
|
|
| 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: 0.2213 |
| - Precision: 0.7501 |
| - Recall: 0.7872 |
| - F1: 0.7682 |
| - Accuracy: 0.9383 |
|
|
| ## 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: 3e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 32 |
| - 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: 3 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.2128 | 1.0 | 6250 | 0.2208 | 0.7484 | 0.7707 | 0.7594 | 0.9361 | |
| | 0.1840 | 2.0 | 12500 | 0.2173 | 0.7375 | 0.7950 | 0.7652 | 0.9366 | |
| | 0.1435 | 3.0 | 18750 | 0.2213 | 0.7501 | 0.7872 | 0.7682 | 0.9383 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.14.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 2.21.0 |
| - Tokenizers 0.22.2 |
| |
