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SloBertAA_Top20_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: 1.0247
- Accuracy: 0.8659
- F1: 0.8642
- Precision: 0.8642
- Recall: 0.8659
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 |
|---|---|---|---|---|---|---|---|
| 0.5972 | 1.0 | 23853 | 0.5451 | 0.8293 | 0.8264 | 0.8276 | 0.8293 |
| 0.4728 | 2.0 | 47706 | 0.5189 | 0.8435 | 0.8380 | 0.8458 | 0.8435 |
| 0.3736 | 3.0 | 71559 | 0.5216 | 0.8512 | 0.8499 | 0.8507 | 0.8512 |
| 0.2785 | 4.0 | 95412 | 0.6074 | 0.8526 | 0.8500 | 0.8528 | 0.8526 |
| 0.2002 | 5.0 | 119265 | 0.6906 | 0.8561 | 0.8534 | 0.8552 | 0.8561 |
| 0.1719 | 6.0 | 143118 | 0.7822 | 0.8600 | 0.8580 | 0.8588 | 0.8600 |
| 0.1337 | 7.0 | 166971 | 0.8742 | 0.8623 | 0.8607 | 0.8612 | 0.8623 |
| 0.0826 | 8.0 | 190824 | 0.9613 | 0.8627 | 0.8602 | 0.8605 | 0.8627 |
| 0.0603 | 9.0 | 214677 | 1.0092 | 0.8632 | 0.8617 | 0.8620 | 0.8632 |
| 0.0359 | 10.0 | 238530 | 1.0247 | 0.8659 | 0.8642 | 0.8642 | 0.8659 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
