final
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:
- Loss: 0.5995
- Accuracy: 0.8444
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.665 | 1.0 | 1494 | 0.6023 | 0.8057 |
| 0.4858 | 2.0 | 2988 | 0.5160 | 0.8318 |
| 0.376 | 3.0 | 4482 | 0.5376 | 0.8353 |
| 0.2863 | 4.0 | 5976 | 0.5591 | 0.8417 |
| 0.2037 | 5.0 | 7470 | 0.5995 | 0.8444 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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