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SloBertAA_Top100_WithOOC_MultilingualBertBase
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3433
- Accuracy: 0.6846
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7277 | 1.0 | 45122 | 1.6629 | 0.5830 |
| 1.4056 | 2.0 | 90244 | 1.4099 | 0.6435 |
| 1.114 | 3.0 | 135366 | 1.3339 | 0.6656 |
| 0.8284 | 4.0 | 180488 | 1.3277 | 0.6780 |
| 0.6761 | 5.0 | 225610 | 1.3433 | 0.6846 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
