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: 1.0886
- 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: 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 | 0.4321 | {'accuracy': 0.87} |
| 0.4477 | 2.0 | 500 | 0.4713 | {'accuracy': 0.863} |
| 0.4477 | 3.0 | 750 | 0.5655 | {'accuracy': 0.877} |
| 0.2184 | 4.0 | 1000 | 0.6685 | {'accuracy': 0.872} |
| 0.2184 | 5.0 | 1250 | 0.7549 | {'accuracy': 0.889} |
| 0.0709 | 6.0 | 1500 | 1.0147 | {'accuracy': 0.885} |
| 0.0709 | 7.0 | 1750 | 0.9756 | {'accuracy': 0.878} |
| 0.024 | 8.0 | 2000 | 1.0414 | {'accuracy': 0.885} |
| 0.024 | 9.0 | 2250 | 1.0876 | {'accuracy': 0.886} |
| 0.0053 | 10.0 | 2500 | 1.0886 | {'accuracy': 0.885} |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.15.0
- Downloads last month
- 3
Model tree for Arifaa/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased