--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: mental_health_model results: [] --- # mental_health_model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6560 - Accuracy: 0.7250 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 8 ### Training results | Training Loss | Epoch | Step | Accuracy | Validation Loss | |:-------------:|:-----:|:----:|:--------:|:---------------:| | No log | 1.0 | 270 | 0.6665 | 0.7627 | | 0.6949 | 2.0 | 540 | 0.6968 | 0.6960 | | 0.6949 | 3.0 | 810 | 0.7038 | 0.6750 | | 0.5696 | 4.0 | 1080 | 0.7185 | 0.6674 | | 0.5696 | 5.0 | 1350 | 0.7136 | 0.6607 | | 0.49 | 6.0 | 1620 | 0.7206 | 0.6531 | | 0.49 | 7.0 | 1890 | 0.7228 | 0.6543 | | 0.4287 | 8.0 | 2160 | 0.6560 | 0.7250 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.0 - Tokenizers 0.15.2