xlm-roberta-base-language-detection-finetuned-ner-finetuned-ner
This model is a fine-tuned version of carexl8/xlm-roberta-base-language-detection-finetuned-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 1.0000
- Recall: 1.0000
- F1: 1.0000
- Accuracy: 1.0000
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0007 | 1.0 | 1543 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0003 | 2.0 | 3086 | 0.0001 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2