--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-lora-text-classification results: [] --- # distilbert-base-uncased-lora-text-classification This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9247 - Accuracy: {'accuracy': 0.886} ## 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 | 0.3986 | {'accuracy': 0.877} | | 0.429 | 2.0 | 500 | 0.5109 | {'accuracy': 0.885} | | 0.429 | 3.0 | 750 | 0.4885 | {'accuracy': 0.884} | | 0.2188 | 4.0 | 1000 | 0.6639 | {'accuracy': 0.882} | | 0.2188 | 5.0 | 1250 | 0.6673 | {'accuracy': 0.882} | | 0.0841 | 6.0 | 1500 | 0.7289 | {'accuracy': 0.895} | | 0.0841 | 7.0 | 1750 | 0.8089 | {'accuracy': 0.887} | | 0.0278 | 8.0 | 2000 | 0.8884 | {'accuracy': 0.88} | | 0.0278 | 9.0 | 2250 | 0.9264 | {'accuracy': 0.884} | | 0.016 | 10.0 | 2500 | 0.9247 | {'accuracy': 0.886} | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1