| --- |
| library_name: transformers |
| base_model: mbeukman/xlm-roberta-base-finetuned-yoruba-finetuned-ner-yoruba |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: mbeukman-finetuned |
| 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. --> |
|
|
| # mbeukman-finetuned |
|
|
| This model is a fine-tuned version of [mbeukman/xlm-roberta-base-finetuned-yoruba-finetuned-ner-yoruba](https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-yoruba-finetuned-ner-yoruba) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1239 |
| - Precision: 0.7778 |
| - Recall: 0.7799 |
| - F1: 0.7789 |
| - Accuracy: 0.9612 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 125 | 0.1634 | 0.7278 | 0.7521 | 0.7397 | 0.9539 | |
| | No log | 2.0 | 250 | 0.1287 | 0.7837 | 0.7772 | 0.7804 | 0.9630 | |
| | No log | 3.0 | 375 | 0.1264 | 0.7609 | 0.7799 | 0.7703 | 0.9598 | |
| | 0.1504 | 4.0 | 500 | 0.1209 | 0.7560 | 0.7939 | 0.7745 | 0.9622 | |
| | 0.1504 | 5.0 | 625 | 0.1239 | 0.7778 | 0.7799 | 0.7789 | 0.9612 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.51.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 2.14.4 |
| - Tokenizers 0.21.1 |
|
|
