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: 1.1580
- Accuracy: 0.8958
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 239 | 3.6296 | 0.6781 |
| No log | 2.0 | 478 | 2.3604 | 0.8158 |
| 3.6983 | 3.0 | 717 | 1.6155 | 0.8668 |
| 3.6983 | 4.0 | 956 | 1.2625 | 0.8910 |
| 1.6887 | 5.0 | 1195 | 1.1580 | 0.8958 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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Model tree for mayankkeshari/distilbert-base-uncased-finetuned-clinc
Base model
distilbert/distilbert-base-uncased