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multibertfinetuned2809
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: 0.3581
- Precision: 0.7138
- Recall: 0.6758
- F1: 0.6943
- Accuracy: 0.8902
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 118 | 0.3829 | 0.6730 | 0.6396 | 0.6559 | 0.8765 |
| No log | 2.0 | 236 | 0.3581 | 0.7138 | 0.6758 | 0.6943 | 0.8902 |
| No log | 3.0 | 354 | 0.3619 | 0.7362 | 0.7104 | 0.7230 | 0.8983 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
