bert-base-cased-azerbaijani
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7046
We thank Microsoft Accelerating Foundation Models Research Program for supporting our research. Authors: Mammad Hajili, Duygu Ataman
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1035 | 0.2500 | 15300 | 0.9753 |
| 0.988 | 0.5000 | 30600 | 0.8985 |
| 0.9276 | 0.7500 | 45900 | 0.8464 |
| 0.8903 | 1.0000 | 61200 | 0.7815 |
| 0.8631 | 1.2500 | 76500 | 0.7778 |
| 0.8435 | 1.5000 | 91800 | 0.7642 |
| 0.8246 | 1.7500 | 107100 | 0.7496 |
| 0.8132 | 2.0000 | 122400 | 0.7372 |
| 0.7999 | 2.2500 | 137700 | 0.7270 |
| 0.7924 | 2.5000 | 153000 | 0.7270 |
| 0.7876 | 2.7500 | 168300 | 0.7178 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
google-bert/bert-base-multilingual-cased