<!-- 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_unweighted_1
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: 1.0985
- F1: {'f1': 0.5363494361475553}
- Accuracy: {'accuracy': 0.6129429892141757}
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 | 0.7291 | {'f1': 0.5311371197568231} | {'accuracy': 0.6604006163328198} |
| 0.7994 | 2.0 | 902 | 0.7153 | {'f1': 0.5663643865301549} | {'accuracy': 0.6619414483821263} |
| 0.6758 | 3.0 | 1353 | 0.7708 | {'f1': 0.5549493182827706} | {'accuracy': 0.6428351309707242} |
| 0.5489 | 4.0 | 1804 | 0.9657 | {'f1': 0.5398498068923226} | {'accuracy': 0.6061633281972265} |
| 0.4078 | 5.0 | 2255 | 1.0339 | {'f1': 0.5356239241887982} | {'accuracy': 0.6138674884437596} |
| 0.3112 | 6.0 | 2706 | 1.0985 | {'f1': 0.5363494361475553} | {'accuracy': 0.6129429892141757} |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
