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xroberta-base-detect-depression-stage-one-ver2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6403
- Accuracy: 0.717
- F1: 0.7893
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-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
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.6432 | 1.0 | 751 | 0.5957 | 0.743 | 0.8219 |
0.6285 | 2.0 | 1502 | 0.5813 | 0.719 | 0.8085 |
0.6165 | 3.0 | 2253 | 0.6459 | 0.7 | 0.7976 |
0.5371 | 4.0 | 3004 | 0.5612 | 0.743 | 0.8120 |
0.46 | 5.0 | 3755 | 0.6403 | 0.717 | 0.7893 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3