--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-ft1500_norm300 results: [] --- # distilbert-base-uncased-finetuned-ft1500_norm300 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: 4.2038 - Mse: 4.2038 - Mae: 1.3920 - R2: 0.4837 - Accuracy: 0.2960 ## 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: 2e-05 - 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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:| | 4.7951 | 1.0 | 3122 | 4.3785 | 4.3785 | 1.4333 | 0.4622 | 0.2832 | | 3.4027 | 2.0 | 6244 | 4.2038 | 4.2038 | 1.3920 | 0.4837 | 0.2960 | ### Framework versions - Transformers 4.21.1 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1