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: 0.9731
- Accuracy: {'accuracy': 0.891}
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.3222 | {'accuracy': 0.895} |
| 0.4357 | 2.0 | 500 | 0.4879 | {'accuracy': 0.872} |
| 0.4357 | 3.0 | 750 | 0.5919 | {'accuracy': 0.895} |
| 0.1751 | 4.0 | 1000 | 0.7484 | {'accuracy': 0.885} |
| 0.1751 | 5.0 | 1250 | 0.7662 | {'accuracy': 0.892} |
| 0.0628 | 6.0 | 1500 | 0.8518 | {'accuracy': 0.88} |
| 0.0628 | 7.0 | 1750 | 0.9047 | {'accuracy': 0.894} |
| 0.0186 | 8.0 | 2000 | 0.9434 | {'accuracy': 0.894} |
| 0.0186 | 9.0 | 2250 | 0.9598 | {'accuracy': 0.895} |
| 0.0083 | 10.0 | 2500 | 0.9731 | {'accuracy': 0.891} |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for phukon/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased