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SloBertAA_Top5_WithOOC_082023
This model is a fine-tuned version of EMBEDDIA/sloberta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7870
- Accuracy: 0.9013
- F1: 0.9010
- Precision: 0.9013
- Recall: 0.9013
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.381 | 1.0 | 10508 | 0.3981 | 0.8665 | 0.8636 | 0.8666 | 0.8665 |
| 0.2912 | 2.0 | 21016 | 0.3497 | 0.8855 | 0.8854 | 0.8868 | 0.8855 |
| 0.2352 | 3.0 | 31524 | 0.3778 | 0.8906 | 0.8901 | 0.8908 | 0.8906 |
| 0.1875 | 4.0 | 42032 | 0.4656 | 0.8903 | 0.8902 | 0.8920 | 0.8903 |
| 0.1447 | 5.0 | 52540 | 0.5620 | 0.8944 | 0.8949 | 0.8969 | 0.8944 |
| 0.0938 | 6.0 | 63048 | 0.6150 | 0.8975 | 0.8975 | 0.8980 | 0.8975 |
| 0.0685 | 7.0 | 73556 | 0.7084 | 0.8950 | 0.8945 | 0.8953 | 0.8950 |
| 0.0449 | 8.0 | 84064 | 0.7499 | 0.8997 | 0.8992 | 0.8995 | 0.8997 |
| 0.0267 | 9.0 | 94572 | 0.7734 | 0.8987 | 0.8983 | 0.8990 | 0.8987 |
| 0.021 | 10.0 | 105080 | 0.7870 | 0.9013 | 0.9010 | 0.9013 | 0.9013 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
