amazon_reviews_finetuning-sentiment-model-3000-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: 1.0099
- Accuracy: 0.58
- F1: 0.5604
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 188 | 0.9821 | 0.59 | 0.5534 |
| No log | 2.0 | 376 | 1.0099 | 0.58 | 0.5604 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Dataset used to train santiviquez/amazon_reviews_finetuning-sentiment-model-3000-samples
Evaluation results
- Accuracy on amazon_reviews_multivalidation set self-reported0.580
- F1 on amazon_reviews_multivalidation set self-reported0.560