Taste-classifier-with-ratings
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4503
- Accuracy: 0.4499
- Recall: 0.4499
- Precision: 0.4499
- F1: 0.4499
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: 5e-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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 1.3342 | 1.0 | 5000 | 1.3867 | 0.4103 | 0.4103 | 0.4103 | 0.4103 |
| 1.1525 | 2.0 | 10000 | 1.3346 | 0.4499 | 0.4499 | 0.4499 | 0.4499 |
| 0.8997 | 3.0 | 15000 | 1.4503 | 0.4499 | 0.4499 | 0.4499 | 0.4499 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2