multilingual_english_SEQUENCE_classification_model
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3810
- Precision: 0.8173
- Recall: 0.8768
- F1: 0.8460
- Accuracy: 0.8404
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 462 | 0.3811 | 0.8293 | 0.8242 | 0.8267 | 0.8273 |
0.4941 | 2.0 | 924 | 0.3810 | 0.8173 | 0.8768 | 0.8460 | 0.8404 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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