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bert-large-uncased-detect-depression-stage-one-v2
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7677
- Accuracy: 0.715
- F1: 0.7912
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-06
- train_batch_size: 4
- eval_batch_size: 4
- 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 | F1 |
|---|---|---|---|---|---|
| 0.597 | 1.0 | 1502 | 0.5699 | 0.718 | 0.8068 |
| 0.5648 | 2.0 | 3004 | 0.6227 | 0.707 | 0.7772 |
| 0.4782 | 3.0 | 4506 | 0.7677 | 0.715 | 0.7912 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
