roberta-depression-detection
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1879
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 9
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.0018 | 1.0 | 629 | 0.2864 |
0.2759 | 2.0 | 1258 | 0.1503 |
0.0554 | 3.0 | 1887 | 0.1445 |
0.1117 | 4.0 | 2516 | 0.1508 |
0.1942 | 5.0 | 3145 | 0.1208 |
0.0018 | 6.0 | 3774 | 0.1527 |
0.0017 | 7.0 | 4403 | 0.2258 |
0.0747 | 8.0 | 5032 | 0.1818 |
0.0006 | 9.0 | 5661 | 0.1879 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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