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SloBertAA_Top10_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: 0.6944
- Accuracy: 0.8730
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 |
---|---|---|---|---|
0.5292 | 1.0 | 16293 | 0.4873 | 0.8400 |
0.4178 | 2.0 | 32586 | 0.4424 | 0.8592 |
0.2963 | 3.0 | 48879 | 0.4757 | 0.8681 |
0.1906 | 4.0 | 65172 | 0.5935 | 0.8706 |
0.143 | 5.0 | 81465 | 0.6944 | 0.8730 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2