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SloBertAA_Top100_WithoutOOC_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: 1.6239
- Accuracy: 0.7550
- F1: 0.7570
- Precision: 0.7629
- Recall: 0.7550
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 |
|---|---|---|---|---|---|---|---|
| 1.349 | 1.0 | 44675 | 1.2964 | 0.6686 | 0.6706 | 0.6858 | 0.6686 |
| 1.0671 | 2.0 | 89350 | 1.1249 | 0.7110 | 0.7157 | 0.7312 | 0.7110 |
| 0.8419 | 3.0 | 134025 | 1.0728 | 0.7297 | 0.7322 | 0.7450 | 0.7297 |
| 0.6419 | 4.0 | 178700 | 1.0672 | 0.7423 | 0.7429 | 0.7504 | 0.7423 |
| 0.5104 | 5.0 | 223375 | 1.1302 | 0.7464 | 0.7480 | 0.7572 | 0.7464 |
| 0.3732 | 6.0 | 268050 | 1.2336 | 0.7492 | 0.7518 | 0.7603 | 0.7492 |
| 0.2934 | 7.0 | 312725 | 1.3301 | 0.7520 | 0.7536 | 0.7604 | 0.7520 |
| 0.2032 | 8.0 | 357400 | 1.4679 | 0.7535 | 0.7550 | 0.7613 | 0.7535 |
| 0.1286 | 9.0 | 402075 | 1.5719 | 0.7546 | 0.7568 | 0.7631 | 0.7546 |
| 0.1133 | 10.0 | 446750 | 1.6239 | 0.7550 | 0.7570 | 0.7629 | 0.7550 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
