amazon-reviews-sentiment-distilbert-base-uncased-6000-samples
This model is a fine-tuned version of distilbert-base-uncased on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:
- Loss: 0.6126
- Accuracy: 0.7355
- F1: 0.6587
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 | 0.6172 | 0.7335 | 0.6516 |
No log | 2.0 | 376 | 0.6126 | 0.7355 | 0.6587 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3
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Model tree for santiviquez/amazon-reviews-sentiment-distilbert-base-uncased-6000-samples
Base model
distilbert/distilbert-base-uncasedDataset used to train santiviquez/amazon-reviews-sentiment-distilbert-base-uncased-6000-samples
Evaluation results
- Accuracy on amazon_reviews_multivalidation set self-reported0.736
- F1 on amazon_reviews_multivalidation set self-reported0.659