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fine-tune-mbert-combined
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2107
- Accuracy: 0.7122
- F1: 0.6796
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: 16
- eval_batch_size: 16
- 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 | F1 |
---|---|---|---|---|---|
0.4817 | 1.0 | 1819 | 0.7004 | 0.6453 | 0.5580 |
0.3926 | 2.0 | 3638 | 0.6305 | 0.6860 | 0.6516 |
0.3086 | 3.0 | 5457 | 0.6903 | 0.7180 | 0.6921 |
0.224 | 4.0 | 7276 | 0.8760 | 0.6977 | 0.6688 |
0.1889 | 5.0 | 9095 | 1.2107 | 0.7122 | 0.6796 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2