output
This model is a fine-tuned version of google/muril-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6250
- Precision: 0.7716
- Recall: 0.7647
- Accuracy: 0.7647
- F1-score: 0.7587
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score |
|---|---|---|---|---|---|---|---|
| 1.7858 | 1.0 | 32 | 1.7821 | 0.0454 | 0.2130 | 0.2130 | 0.0748 |
| 1.7526 | 2.0 | 64 | 1.7539 | 0.1754 | 0.2860 | 0.2860 | 0.1866 |
| 1.7112 | 3.0 | 96 | 1.7232 | 0.3352 | 0.3043 | 0.3043 | 0.2168 |
| 1.6655 | 4.0 | 128 | 1.6832 | 0.7122 | 0.6166 | 0.6166 | 0.6194 |
| 1.6217 | 5.0 | 160 | 1.6496 | 0.7708 | 0.7688 | 0.7688 | 0.7629 |
| 1.5898 | 6.0 | 192 | 1.6431 | 0.7618 | 0.7424 | 0.7424 | 0.7379 |
| 1.5678 | 7.0 | 224 | 1.6285 | 0.7697 | 0.7627 | 0.7627 | 0.7565 |
| 1.5572 | 8.0 | 256 | 1.6250 | 0.7716 | 0.7647 | 0.7647 | 0.7587 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google/muril-base-cased