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xlm-roberta-large-v10-ES-ner
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4403
- Precision: 0.6980
- Recall: 0.7355
- F1: 0.7163
- Accuracy: 0.9175
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.409 | 1.75 | 500 | 0.2883 | 0.6210 | 0.6839 | 0.6509 | 0.9128 |
| 0.1887 | 3.5 | 1000 | 0.3057 | 0.6931 | 0.7045 | 0.6988 | 0.9198 |
| 0.1129 | 5.24 | 1500 | 0.3827 | 0.6490 | 0.7066 | 0.6766 | 0.9099 |
| 0.0645 | 6.99 | 2000 | 0.3905 | 0.6815 | 0.7293 | 0.7046 | 0.9159 |
| 0.0335 | 8.74 | 2500 | 0.4403 | 0.6980 | 0.7355 | 0.7163 | 0.9175 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
