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bert-base-multilingual-cased-finetuned-cola
This model is a fine-tuned version of bert-base-multilingual-cased on an unkown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1729
- Accuracy: 0.9755
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 |
|---|---|---|---|---|
| 0.5119 | 1.0 | 625 | 0.2386 | 0.922 |
| 0.2536 | 2.0 | 1250 | 0.2055 | 0.949 |
| 0.1718 | 3.0 | 1875 | 0.1733 | 0.969 |
| 0.0562 | 4.0 | 2500 | 0.1661 | 0.974 |
| 0.0265 | 5.0 | 3125 | 0.1729 | 0.9755 |
Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
