--- license: mit base_model: roberta-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: roberta-base-detect-cheapfake-combined-train-test-10200-2-8 results: [] --- # roberta-base-detect-cheapfake-combined-train-test-10200-2-8 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5062 - Accuracy: 0.875 - F1: 0.8619 ## 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: 5e-06 - train_batch_size: 32 - eval_batch_size: 32 - 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 | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 319 | 0.6261 | 0.69 | 0.5571 | | 0.1573 | 2.0 | 638 | 0.4591 | 0.88 | 0.8696 | | 0.1573 | 3.0 | 957 | 0.5378 | 0.82 | 0.8302 | | 0.0598 | 4.0 | 1276 | 0.5968 | 0.85 | 0.8276 | | 0.0471 | 5.0 | 1595 | 0.5062 | 0.875 | 0.8619 | ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.1.0 - Tokenizers 0.15.1