Cheese_xray
This model is a fine-tuned version of barghavani/Cheese_xray on the chest-xray-classification dataset. It achieves the following results on the evaluation set:
- Loss: 0.2827
- Accuracy: 0.8883
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3993 | 0.99 | 63 | 0.4364 | 0.7165 |
| 0.3454 | 1.99 | 127 | 0.3947 | 0.7680 |
| 0.3327 | 3.0 | 191 | 0.3582 | 0.8591 |
| 0.3329 | 4.0 | 255 | 0.3371 | 0.8746 |
| 0.2992 | 4.99 | 318 | 0.3449 | 0.8643 |
| 0.3289 | 5.99 | 382 | 0.3172 | 0.8832 |
| 0.3309 | 7.0 | 446 | 0.2956 | 0.8935 |
| 0.2875 | 8.0 | 510 | 0.2911 | 0.8883 |
| 0.2764 | 8.99 | 573 | 0.2884 | 0.9124 |
| 0.265 | 9.88 | 630 | 0.2827 | 0.8883 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0