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aspect_extraction_laptop_reviews
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: 0.1003
- Precision: 0.7872
- Recall: 0.7817
- F1: 0.7845
- Accuracy: 0.9732
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 362 | 0.0854 | 0.7070 | 0.7817 | 0.7425 | 0.9675 |
| 0.1121 | 2.0 | 724 | 0.0937 | 0.7466 | 0.7676 | 0.7569 | 0.9696 |
| 0.0383 | 3.0 | 1086 | 0.0959 | 0.7622 | 0.7676 | 0.7649 | 0.9714 |
| 0.0383 | 4.0 | 1448 | 0.1003 | 0.7872 | 0.7817 | 0.7845 | 0.9732 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.2
- Tokenizers 0.13.3
