metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mental_classification
results: []
mental_classification
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5913
- Accuracy: 0.8815
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2665 | 1.5038 | 197 | 1.6089 | 0.5908 |
| 1.1385 | 3.0076 | 394 | 1.0268 | 0.7610 |
| 0.5896 | 4.5115 | 591 | 0.7455 | 0.8394 |
| 0.3186 | 6.0153 | 788 | 0.6275 | 0.8566 |
| 0.1691 | 7.5191 | 985 | 0.5975 | 0.8719 |
| 0.0971 | 9.0229 | 1182 | 0.5844 | 0.8623 |
| 0.0597 | 10.5267 | 1379 | 0.5824 | 0.8757 |
| 0.0418 | 12.0305 | 1576 | 0.5894 | 0.8776 |
| 0.0334 | 13.5344 | 1773 | 0.5913 | 0.8815 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1