finetuned_model_sentiment_analysis_yelp
This model is a fine-tuned version of distilbert-base-cased on the yelp_review_full dataset. It achieves the following results on the evaluation set:
- Loss: 0.8933
- Precision: 0.6404
- Recall: 0.6409
- F1: 0.6405
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.8691 | 1.0 | 3657 | 0.8801 | 0.6224 | 0.6201 | 0.6149 |
| 0.7506 | 2.0 | 7314 | 0.8469 | 0.6458 | 0.6421 | 0.6428 |
| 0.6087 | 3.0 | 10971 | 0.8933 | 0.6404 | 0.6409 | 0.6405 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2