distilbert-base-cased-finetuned-patient-doctor-text-classifier-eng-multilingual
This model is a fine-tuned version of lxyuan/distilbert-base-multilingual-cased-sentiments-student on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0988
- Accuracy: 0.9851
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1049 | 1.0 | 1547 | 0.0713 | 0.9819 |
0.0442 | 2.0 | 3094 | 0.0751 | 0.9833 |
0.0307 | 3.0 | 4641 | 0.0699 | 0.9856 |
0.0231 | 4.0 | 6188 | 0.0889 | 0.9844 |
0.0188 | 5.0 | 7735 | 0.0898 | 0.9852 |
0.0169 | 6.0 | 9282 | 0.0974 | 0.9831 |
0.0138 | 7.0 | 10829 | 0.0954 | 0.9852 |
0.0124 | 8.0 | 12376 | 0.0986 | 0.9845 |
0.0108 | 9.0 | 13923 | 0.0959 | 0.9846 |
0.0095 | 10.0 | 15470 | 0.0988 | 0.9851 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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