--- base_model: distilbert-base-uncased library_name: peft license: apache-2.0 metrics: - accuracy tags: - generated_from_trainer 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: 0.2711 - Accuracy: {'accuracy': 0.903} ## 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: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:-------------------:| | No log | 1.0 | 16 | 0.3245 | {'accuracy': 0.886} | | No log | 2.0 | 32 | 0.2693 | {'accuracy': 0.892} | | No log | 3.0 | 48 | 0.2717 | {'accuracy': 0.887} | | No log | 4.0 | 64 | 0.2650 | {'accuracy': 0.898} | | No log | 5.0 | 80 | 0.2711 | {'accuracy': 0.903} | ### Framework versions - PEFT 0.13.2 - Transformers 4.44.2 - Pytorch 2.5.0+cu121 - Datasets 3.1.0 - Tokenizers 0.19.1