amazon-reviews-sentiment-bert-base-uncased-6000-samples
This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:
- Loss: 0.5890
- Accuracy: 0.7679
- F1: 0.7168
Predicted labels
- LABEL_0: Negative review
- LABEL_1: Neutral review
- LABEL_2: Positive review
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 188 | 0.5745 | 0.7586 | 0.7149 |
| No log | 2.0 | 376 | 0.5890 | 0.7679 | 0.7168 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3
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Evaluation results
- Accuracy on amazon_reviews_multivalidation set self-reported0.768
- F1 on amazon_reviews_multivalidation set self-reported0.717