--- license: apache-2.0 tags: - text-classification - depression - reddit - generated_from_trainer datasets: - mrjunos/depression-reddit-cleaned metrics: - accuracy widget: - text: ["i just found out my boyfriend is depressed i really want to be there for him but i feel like i ve only been saying the wrong thing how can i be there for him help him and see him get better i m worried it will continue to the point it will consume him i can already see his personality changing and i m scared for the future what thing can i say or do to comfort or help"] example_title: depression - text: ["i m getting more and more people asking where they can buy the ambients album simple answer is quot not yet quot it ll be on itunes eventually"] example_title: not_depression model-index: - name: depression-reddit-distilroberta-base results: - task: name: Text Classification type: text-classification dataset: name: mrjunos/depression-reddit-cleaned type: depression-reddit-cleaned config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9715578539107951 --- # depression-reddit-distilroberta-base This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the mrjunos/depression-reddit-cleaned dataset. It achieves the following results on the evaluation set: - Loss: 0.0821 - Accuracy: 0.9716 ## 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-05 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1711 | 0.65 | 500 | 0.0821 | 0.9716 | | 0.1022 | 1.29 | 1000 | 0.1148 | 0.9709 | | 0.0595 | 1.94 | 1500 | 0.1178 | 0.9787 | | 0.0348 | 2.59 | 2000 | 0.0951 | 0.9851 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.0.1+cu118 - Datasets 2.13.0 - Tokenizers 0.13.3