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bert-large-uncased-detect-depression-stage-one-v4
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: 0.7637
- Accuracy: 0.717
- F1: 0.7838
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 |
|---|---|---|---|---|---|
| 0.5824 | 1.0 | 1502 | 0.5673 | 0.726 | 0.7832 |
| 0.5499 | 2.0 | 3004 | 0.6104 | 0.725 | 0.7976 |
| 0.486 | 3.0 | 4506 | 0.7637 | 0.717 | 0.7838 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
