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SloBertAA_Top100_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: 1.6326
- Accuracy: 0.7431
- F1: 0.7447
- Precision: 0.7503
- Recall: 0.7431
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 |
|---|---|---|---|---|---|---|---|
| 1.5143 | 1.0 | 45122 | 1.4964 | 0.6272 | 0.6264 | 0.6488 | 0.6272 |
| 1.2462 | 2.0 | 90244 | 1.2729 | 0.6811 | 0.6814 | 0.7043 | 0.6811 |
| 1.0236 | 3.0 | 135366 | 1.2134 | 0.7012 | 0.7027 | 0.7211 | 0.7012 |
| 0.7721 | 4.0 | 180488 | 1.1976 | 0.7179 | 0.7204 | 0.7357 | 0.7179 |
| 0.6597 | 5.0 | 225610 | 1.1953 | 0.7321 | 0.7324 | 0.7406 | 0.7321 |
| 0.4816 | 6.0 | 270732 | 1.2776 | 0.7303 | 0.7330 | 0.7444 | 0.7303 |
| 0.4039 | 7.0 | 315854 | 1.3625 | 0.7363 | 0.7379 | 0.7451 | 0.7363 |
| 0.2845 | 8.0 | 360976 | 1.4677 | 0.7395 | 0.7407 | 0.7470 | 0.7395 |
| 0.2192 | 9.0 | 406098 | 1.5720 | 0.7422 | 0.7434 | 0.7488 | 0.7422 |
| 0.1689 | 10.0 | 451220 | 1.6326 | 0.7431 | 0.7447 | 0.7503 | 0.7431 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
