model-mental-health-classification
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1549
- Accuracy: 0.5855
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.1217 | 1.0 | 1642 | 1.1627 | 0.5653 |
0.9457 | 2.0 | 3284 | 1.1549 | 0.5855 |
0.6765 | 3.0 | 4926 | 1.2525 | 0.5725 |
0.487 | 4.0 | 6568 | 1.4481 | 0.5718 |
0.3557 | 5.0 | 8210 | 1.5812 | 0.5639 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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