deberta-finetuned-ner-finetuned-ner
This model is a fine-tuned version of baptiste/deberta-finetuned-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7964
- Precision: 0.6210
- Recall: 0.3188
- F1: 0.4213
- Accuracy: 0.8212
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 1.0763 | 0.5583 | 0.1387 | 0.2222 | 0.7916 |
| No log | 2.0 | 8 | 0.8910 | 0.8108 | 0.3106 | 0.4491 | 0.8212 |
| No log | 3.0 | 12 | 0.7964 | 0.6210 | 0.3188 | 0.4213 | 0.8212 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2