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week5-eng-distilbert-base-multilingual-cased-finetuned
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0855
- Precision: 0.2813
- Recall: 0.2949
- F1: 0.2880
- Accuracy: 0.9763
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: 8
- eval_batch_size: 8
- 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 |
---|---|---|---|---|---|---|---|
0.1071 | 1.0 | 924 | 0.0911 | 0.2472 | 0.0444 | 0.0753 | 0.9755 |
0.07 | 2.0 | 1848 | 0.0891 | 0.3206 | 0.1697 | 0.2219 | 0.9775 |
0.0522 | 3.0 | 2772 | 0.0855 | 0.2813 | 0.2949 | 0.2880 | 0.9763 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1