yelp_lora_output
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0541
- Accuracy: 0.519
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4661 | 1.0 | 125 | 1.4022 | 0.373 |
| 1.0935 | 2.0 | 250 | 1.0773 | 0.514 |
| 1.2359 | 3.0 | 375 | 1.0541 | 0.519 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.2.0
- Tokenizers 0.22.1
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Model tree for zzplus1/bert-lora-yelp-sentiment
Base model
google-bert/bert-base-cased