distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5645
- Accuracy: {'accuracy': 0.885}
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: 0.001
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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 |
|---|---|---|---|---|
| No log | 1.0 | 334 | 0.5487 | {'accuracy': 0.863} |
| 0.4823 | 2.0 | 668 | 0.4822 | {'accuracy': 0.884} |
| 0.2578 | 3.0 | 1002 | 0.5645 | {'accuracy': 0.885} |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cpu
- Datasets 3.1.0
- Tokenizers 0.21.0
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Model tree for lunablue/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased