distilbert-base-uncased-distilled-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: 0.3505
- Accuracy: 0.9468
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: 9
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 318 | 2.3157 | 0.7303 |
2.7298 | 2.0 | 636 | 1.1956 | 0.8648 |
2.7298 | 3.0 | 954 | 0.6761 | 0.9126 |
1.0591 | 4.0 | 1272 | 0.4801 | 0.9319 |
0.4685 | 5.0 | 1590 | 0.4043 | 0.9403 |
0.4685 | 6.0 | 1908 | 0.3768 | 0.9416 |
0.3124 | 7.0 | 2226 | 0.3614 | 0.9445 |
0.2623 | 8.0 | 2544 | 0.3523 | 0.9452 |
0.2623 | 9.0 | 2862 | 0.3505 | 0.9468 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 7