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SloBertAA_Top10_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: 0.7250
- Accuracy: 0.9087
- F1: 0.9077
- Precision: 0.9076
- Recall: 0.9087
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 |
|---|---|---|---|---|---|---|---|
| 0.3963 | 1.0 | 16293 | 0.3859 | 0.8775 | 0.8765 | 0.8784 | 0.8775 |
| 0.3207 | 2.0 | 32586 | 0.3425 | 0.8928 | 0.8928 | 0.8949 | 0.8928 |
| 0.2433 | 3.0 | 48879 | 0.3723 | 0.9011 | 0.8995 | 0.8999 | 0.9011 |
| 0.1874 | 4.0 | 65172 | 0.4615 | 0.9018 | 0.8999 | 0.9004 | 0.9018 |
| 0.1537 | 5.0 | 81465 | 0.5215 | 0.9026 | 0.9011 | 0.9014 | 0.9026 |
| 0.1136 | 6.0 | 97758 | 0.5769 | 0.9044 | 0.9027 | 0.9029 | 0.9044 |
| 0.067 | 7.0 | 114051 | 0.6370 | 0.9060 | 0.9039 | 0.9041 | 0.9060 |
| 0.0514 | 8.0 | 130344 | 0.6676 | 0.9058 | 0.9047 | 0.9049 | 0.9058 |
| 0.0275 | 9.0 | 146637 | 0.7306 | 0.9064 | 0.9054 | 0.9061 | 0.9064 |
| 0.0243 | 10.0 | 162930 | 0.7250 | 0.9087 | 0.9077 | 0.9076 | 0.9087 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
