<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
depression_classifier_weighted_2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0299
- F1: {'f1': 0.5274571619747097}
- Accuracy: {'accuracy': 0.5993836671802774}
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: 2e-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
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| No log | 1.0 | 451 | 0.9802 | {'f1': 0.48800261330578315} | {'accuracy': 0.561171032357473} |
| 0.8742 | 2.0 | 902 | 0.8159 | {'f1': 0.5567921899894229} | {'accuracy': 0.636055469953775} |
| 0.7241 | 3.0 | 1353 | 0.8759 | {'f1': 0.5323551976865734} | {'accuracy': 0.5950693374422188} |
| 0.5999 | 4.0 | 1804 | 1.0016 | {'f1': 0.5186059710481855} | {'accuracy': 0.5685670261941448} |
| 0.465 | 5.0 | 2255 | 1.0535 | {'f1': 0.5143537550061232} | {'accuracy': 0.5722650231124807} |
| 0.3788 | 6.0 | 2706 | 1.0299 | {'f1': 0.5274571619747097} | {'accuracy': 0.5993836671802774} |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
