NER-finetuning-BETO-PRO
This model is a fine-tuned version of NazaGara/NER-fine-tuned-BETO on the conll2002 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1561
- Precision: 0.8319
- Recall: 0.8520
- F1: 0.8419
- Accuracy: 0.9707
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0462 | 1.0 | 1041 | 0.1448 | 0.8335 | 0.8594 | 0.8462 | 0.9712 |
| 0.0241 | 2.0 | 2082 | 0.1561 | 0.8319 | 0.8520 | 0.8419 | 0.9707 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Base model
NazaGara/NER-fine-tuned-BETODataset used to train raulgdp/NER-finetuning-BETO-PRO
Evaluation results
- Precision on conll2002validation set self-reported0.832
- Recall on conll2002validation set self-reported0.852
- F1 on conll2002validation set self-reported0.842
- Accuracy on conll2002validation set self-reported0.971