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SloBertAA_Top50_WithoutOOC_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: 0.9867
- Accuracy: 0.7690
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 |
|---|---|---|---|---|
| 1.1549 | 1.0 | 32692 | 1.1139 | 0.6885 |
| 0.9075 | 2.0 | 65384 | 0.9769 | 0.7307 |
| 0.6662 | 3.0 | 98076 | 0.9210 | 0.7531 |
| 0.5019 | 4.0 | 130768 | 0.9354 | 0.7648 |
| 0.3155 | 5.0 | 163460 | 0.9867 | 0.7690 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
