rubert-tiny2-finetuned-ner
This model was trained from scratch on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2259
- Precision: 0.7137
- Recall: 0.7271
- F1: 0.7203
- Accuracy: 0.9363
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 |
|---|
| 0.6327 | 1.0 | 878 | 0.3218 | 0.6068 | 0.6009 | 0.6038 | 0.9114 |
| 0.2937 | 2.0 | 1756 | 0.2434 | 0.6864 | 0.7013 | 0.6938 | 0.9307 |
| 0.2357 | 3.0 | 2634 | 0.2259 | 0.7137 | 0.7271 | 0.7203 | 0.9363 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
