metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mental_health_model
results: []
mental_health_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4142
- Accuracy: 0.7504
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 270 | 0.6937 | 0.6957 |
| 0.7345 | 2.0 | 540 | 0.6217 | 0.7401 |
| 0.7345 | 3.0 | 810 | 0.6691 | 0.7428 |
| 0.346 | 4.0 | 1080 | 0.7451 | 0.7537 |
| 0.346 | 5.0 | 1350 | 0.9557 | 0.7461 |
| 0.1315 | 6.0 | 1620 | 1.1519 | 0.7515 |
| 0.1315 | 7.0 | 1890 | 1.2995 | 0.7369 |
| 0.0472 | 8.0 | 2160 | 1.4142 | 0.7396 |
| 0.0472 | 9.0 | 2430 | 1.4000 | 0.7499 |
| 0.0226 | 10.0 | 2700 | 1.4142 | 0.7504 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2