amazon-reviews-finetuning-bert-base-sentiment
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: 1.0136
- Accuracy: 0.5764
- F1: 0.5739
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 |
|---|---|---|---|---|---|
| 0.9867 | 1.0 | 1563 | 0.9814 | 0.5792 | 0.5677 |
| 0.8435 | 2.0 | 3126 | 1.0136 | 0.5764 | 0.5739 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for santiviquez/amazon-reviews-finetuning-bert-base-sentiment
Dataset used to train santiviquez/amazon-reviews-finetuning-bert-base-sentiment
Evaluation results
- Accuracy on amazon_reviews_multivalidation set self-reported0.576
- F1 on amazon_reviews_multivalidation set self-reported0.574