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bert-based-multilingual-cased-finetuned-lid-model-1lk
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: 0.0492
- Precision: 0.9551
- Recall: 0.9522
- F1: 0.9537
- Accuracy: 0.9843
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0801 | 1.0 | 11007 | 0.0725 | 0.9331 | 0.9191 | 0.9260 | 0.9750 |
0.0515 | 2.0 | 22014 | 0.0522 | 0.9494 | 0.9421 | 0.9457 | 0.9818 |
0.0355 | 3.0 | 33021 | 0.0492 | 0.9551 | 0.9522 | 0.9537 | 0.9843 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3