| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: DepressionAnalysis |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # DepressionAnalysis |
|
|
| 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: 0.4023 |
| - Accuracy: 0.8367 |
|
|
| ## 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: 48 |
| - eval_batch_size: 48 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.6091 | 1.0 | 151 | 0.5593 | 0.7082 | |
| | 0.4041 | 2.0 | 302 | 0.4295 | 0.8055 | |
| | 0.3057 | 3.0 | 453 | 0.4023 | 0.8367 | |
| | 0.1921 | 4.0 | 604 | 0.4049 | 0.8454 | |
| | 0.1057 | 5.0 | 755 | 0.4753 | 0.8479 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.20.1 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.3.2 |
| - Tokenizers 0.12.1 |
| |
