bert-f1-durga-muhammad-c
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0245 | 1.0 | 42 | 0.0241 | 0.995 | 0.995 | 0.995 | 0.995 |
| 0.0032 | 2.0 | 84 | 0.0081 | 0.999 | 0.999 | 0.999 | 0.999 |
| 0.0011 | 3.0 | 126 | 0.0075 | 0.999 | 0.999 | 0.999 | 0.999 |
| 0.0008 | 4.0 | 168 | 0.0068 | 0.999 | 0.999 | 0.999 | 0.999 |
| 0.0006 | 5.0 | 210 | 0.0078 | 0.999 | 0.999 | 0.999 | 0.999 |
| 0.0012 | 6.0 | 252 | 0.0063 | 0.999 | 0.999 | 0.999 | 0.999 |
| 0.0022 | 7.0 | 294 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0004 | 8.0 | 336 | 0.0031 | 0.999 | 0.999 | 0.999 | 0.999 |
| 0.0003 | 9.0 | 378 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 10.0 | 420 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 11.0 | 462 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 12.0 | 504 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 13.0 | 546 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 14.0 | 588 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 15.0 | 630 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 16.0 | 672 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 17.0 | 714 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1