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distilbert-base-uncased_intent_classification
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: 10.1998
- F1: 0.0560
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: 16
- eval_batch_size: 16
- 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 312 | 7.5574 | 0.058 |
| 0.458 | 2.0 | 624 | 8.9497 | 0.0560 |
| 0.458 | 3.0 | 936 | 9.6656 | 0.0560 |
| 0.0848 | 4.0 | 1248 | 10.0615 | 0.058 |
| 0.0379 | 5.0 | 1560 | 10.1998 | 0.0560 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
