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xlm-roberta-base-it-aug-ner
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2626
- Precision: 0.6778
- Recall: 0.6981
- F1: 0.6878
- Accuracy: 0.9266
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6114 | 1.0 | 882 | 0.3615 | 0.5708 | 0.5680 | 0.5694 | 0.9023 |
| 0.2401 | 2.0 | 1764 | 0.2841 | 0.6274 | 0.6674 | 0.6468 | 0.9170 |
| 0.1886 | 3.0 | 2646 | 0.2720 | 0.6580 | 0.6853 | 0.6713 | 0.9224 |
| 0.1594 | 4.0 | 3528 | 0.2626 | 0.6778 | 0.6981 | 0.6878 | 0.9266 |
| 0.1454 | 5.0 | 4410 | 0.2632 | 0.6660 | 0.6974 | 0.6813 | 0.9257 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
