--- license: mit base_model: roberta-large tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: roberta-large-detect-dep-v3 results: [] --- # roberta-large-detect-dep-v3 This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6359 - Accuracy: 0.713 - F1: 0.7817 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.6348 | 1.0 | 751 | 0.5414 | 0.769 | 0.8241 | | 0.5428 | 2.0 | 1502 | 0.5873 | 0.733 | 0.8027 | | 0.4829 | 3.0 | 2253 | 0.6359 | 0.713 | 0.7817 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.13.1 - Tokenizers 0.13.3