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DepressionAnalysis
This model is a fine-tuned version of 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
