roberta-depression-detection-v3
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1845
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 15
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.1604 | 1.0 | 219 | 0.2178 |
0.1672 | 2.0 | 438 | 0.2603 |
0.0986 | 3.0 | 657 | 0.1845 |
0.061 | 4.0 | 876 | 0.2380 |
0.0015 | 5.0 | 1095 | 0.2370 |
0.0648 | 6.0 | 1314 | 0.3222 |
0.0008 | 7.0 | 1533 | 0.2871 |
0.0488 | 8.0 | 1752 | 0.3489 |
0.0003 | 9.0 | 1971 | 0.3433 |
0.0488 | 10.0 | 2190 | 0.3191 |
0.0004 | 11.0 | 2409 | 0.3237 |
0.0003 | 12.0 | 2628 | 0.3337 |
0.0003 | 13.0 | 2847 | 0.3626 |
0.0004 | 14.0 | 3066 | 0.2966 |
0.0004 | 15.0 | 3285 | 0.2928 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.1.0+cpu
- Datasets 2.10.1
- Tokenizers 0.13.2
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