bert_ftopt_ner_model2
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2229
- Precision: 0.6226
- Recall: 0.7279
- F1: 0.6712
- Accuracy: 0.9568
- Macro F1: 0.6160
- Micro F1: 0.9568
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: 1.3945997553042204e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Macro F1 | Micro F1 |
|---|
| No log | 1.0 | 249 | 0.2657 | 0.5313 | 0.6762 | 0.5950 | 0.9414 | 0.5854 | 0.9414 |
| No log | 2.0 | 498 | 0.2832 | 0.5777 | 0.6849 | 0.6268 | 0.9452 | 0.6161 | 0.9452 |
| 0.0393 | 3.0 | 747 | 0.2986 | 0.5564 | 0.6959 | 0.6184 | 0.9439 | 0.6142 | 0.9439 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
