distilbert-base-uncased-finetuned-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2804
- Accuracy: 0.8845
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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
4.3292 | 1.0 | 318 | 3.3607 | 0.7158 |
2.7628 | 2.0 | 636 | 2.0645 | 0.8416 |
1.8038 | 3.0 | 954 | 1.4528 | 0.8761 |
1.3955 | 4.0 | 1272 | 1.2804 | 0.8845 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3
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Model tree for simonmok/distilbert-base-uncased-finetuned-clinc
Base model
distilbert/distilbert-base-uncased