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20231005-2-bert-base-multilingual-cased-new
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.6479
- Loss: 1.6281
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 2.8918 | 1.82 | 200 | 0.4038 | 2.4903 |
| 2.3882 | 3.64 | 400 | 0.4978 | 2.2096 |
| 2.1785 | 5.45 | 600 | 0.4934 | 1.9995 |
| 2.0686 | 7.27 | 800 | 0.5386 | 2.0103 |
| 1.9575 | 9.09 | 1000 | 0.5243 | 2.1245 |
| 1.8828 | 10.91 | 1200 | 0.5932 | 1.7872 |
| 1.8112 | 12.73 | 1400 | 0.6204 | 1.4894 |
| 1.7449 | 14.55 | 1600 | 0.5978 | 1.7968 |
| 1.6916 | 16.36 | 1800 | 0.6253 | 1.6254 |
| 1.6763 | 18.18 | 2000 | 0.6377 | 1.4638 |
| 1.6459 | 20.0 | 2200 | 0.6479 | 1.6281 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
