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token_fine_tunned_flipkart_2
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: 0.3435
- Precision: 0.8797
- Recall: 0.9039
- F1: 0.8916
- Accuracy: 0.9061
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 109 | 0.5647 | 0.7398 | 0.8123 | 0.7744 | 0.8111 |
| No log | 2.0 | 218 | 0.3863 | 0.8165 | 0.8751 | 0.8448 | 0.8716 |
| No log | 3.0 | 327 | 0.3367 | 0.8599 | 0.8847 | 0.8721 | 0.8869 |
| No log | 4.0 | 436 | 0.3266 | 0.8688 | 0.8911 | 0.8798 | 0.8977 |
| 0.527 | 5.0 | 545 | 0.3508 | 0.8595 | 0.8898 | 0.8744 | 0.8909 |
| 0.527 | 6.0 | 654 | 0.3410 | 0.8748 | 0.9045 | 0.8894 | 0.9009 |
| 0.527 | 7.0 | 763 | 0.3431 | 0.8754 | 0.9045 | 0.8897 | 0.9049 |
| 0.527 | 8.0 | 872 | 0.3435 | 0.8797 | 0.9039 | 0.8916 | 0.9061 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1
