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textClass-finetuned-coba-conf-orang
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4868
- Accuracy: 0.7856
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: 1e-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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5108 | 1.0 | 2757 | 0.4652 | 0.7761 |
0.4484 | 2.0 | 5514 | 0.4447 | 0.7881 |
0.4031 | 3.0 | 8271 | 0.4552 | 0.7891 |
0.3646 | 4.0 | 11028 | 0.4720 | 0.7911 |
0.3372 | 5.0 | 13785 | 0.4868 | 0.7856 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2