--- 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: 1.4142 - Accuracy: 0.7504 ## 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 270 | 0.6937 | 0.6957 | | 0.7345 | 2.0 | 540 | 0.6217 | 0.7401 | | 0.7345 | 3.0 | 810 | 0.6691 | 0.7428 | | 0.346 | 4.0 | 1080 | 0.7451 | 0.7537 | | 0.346 | 5.0 | 1350 | 0.9557 | 0.7461 | | 0.1315 | 6.0 | 1620 | 1.1519 | 0.7515 | | 0.1315 | 7.0 | 1890 | 1.2995 | 0.7369 | | 0.0472 | 8.0 | 2160 | 1.4142 | 0.7396 | | 0.0472 | 9.0 | 2430 | 1.4000 | 0.7499 | | 0.0226 | 10.0 | 2700 | 1.4142 | 0.7504 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2