bert-base-multilingual-cased-ibo
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1290
- Accuracy: 0.7616
- F1 Binary: 0.4514
- Precision: 0.3301
- Recall: 0.7137
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: 3e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 43
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 1.0 | 216 | 0.1559 | 0.4867 | 0.3151 | 0.1929 | 0.8589 |
No log | 2.0 | 432 | 0.1397 | 0.5992 | 0.3519 | 0.2262 | 0.7916 |
0.1407 | 3.0 | 648 | 0.1235 | 0.7141 | 0.4175 | 0.2899 | 0.7453 |
0.1407 | 4.0 | 864 | 0.1290 | 0.7616 | 0.4514 | 0.3301 | 0.7137 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
google-bert/bert-base-multilingual-cased