--- license: mit base_model: roberta-large tags: - generated_from_trainer metrics: - accuracy model-index: - name: roberta-large-depression-classification-v2 results: [] --- # roberta-large-depression-classification-v2 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: 2.2328 - Accuracy: 0.5435 - F1 Score: 0.5316 ## 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: 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| | 0.9778 | 1.0 | 677 | 1.2323 | 0.5380 | 0.5275 | | 0.6377 | 2.0 | 1354 | 2.0223 | 0.5315 | 0.5125 | | 0.5285 | 3.0 | 2031 | 2.2328 | 0.5435 | 0.5316 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3