berttest2
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0674
- Precision: 0.9138
- Recall: 0.9325
- F1: 0.9230
- Accuracy: 0.9823
Model description
Model implemented for CSE 573 Course Project
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0869 | 1.0 | 1756 | 0.0674 | 0.9138 | 0.9325 | 0.9230 | 0.9823 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cpu
- Datasets 2.6.1
- Tokenizers 0.13.2