bbc
This model is a fine-tuned version of bert-base-cased on the yelp_review_full dataset. It achieves the following results on the evaluation set:
- Loss: 1.1692
- Accuracy: 0.499
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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 250 | 1.4265 | 0.391 |
| 1.4806 | 2.0 | 500 | 1.2233 | 0.458 |
| 1.4806 | 3.0 | 750 | 1.1692 | 0.499 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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Model tree for Kerz/bbc
Base model
google-bert/bert-base-casedDataset used to train Kerz/bbc
Evaluation results
- Accuracy on yelp_review_fulltest set self-reported0.499