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distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.3223
- Accuracy: 0.9510
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: 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 |
---|---|---|---|---|
No log | 1.0 | 318 | 2.0952 | 0.7513 |
2.4883 | 2.0 | 636 | 1.0578 | 0.8613 |
2.4883 | 3.0 | 954 | 0.5967 | 0.9184 |
0.9387 | 4.0 | 1272 | 0.4331 | 0.9361 |
0.4221 | 5.0 | 1590 | 0.3734 | 0.9445 |
0.4221 | 6.0 | 1908 | 0.3483 | 0.9481 |
0.2906 | 7.0 | 2226 | 0.3332 | 0.9506 |
0.2464 | 8.0 | 2544 | 0.3274 | 0.9494 |
0.2464 | 9.0 | 2862 | 0.3245 | 0.9506 |
0.2315 | 10.0 | 3180 | 0.3223 | 0.9510 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3