metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: microsoft/swin-large-patch4-window7-224-in22k
model-index:
- name: chest-swin-large-finetuned
results: []
chest-swin-large-finetuned
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224-in22k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1159
- Accuracy: 0.9588
- Precision: 0.9599
- Recall: 0.9401
- F1: 0.9492
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: 0.005
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3305 | 0.99 | 63 | 0.1600 | 0.9365 | 0.9478 | 0.8868 | 0.9119 |
| 0.2335 | 1.99 | 127 | 0.1552 | 0.9313 | 0.8968 | 0.9472 | 0.9166 |
| 0.1977 | 3.0 | 191 | 0.0855 | 0.9734 | 0.9608 | 0.9714 | 0.9659 |
| 0.1746 | 4.0 | 255 | 0.0870 | 0.9794 | 0.9794 | 0.9669 | 0.9729 |
| 0.1797 | 4.99 | 318 | 0.0829 | 0.9700 | 0.9549 | 0.9690 | 0.9617 |
| 0.1436 | 5.99 | 382 | 0.0797 | 0.9708 | 0.9556 | 0.9707 | 0.9628 |
| 0.1632 | 7.0 | 446 | 0.0816 | 0.9700 | 0.9508 | 0.9754 | 0.9621 |
| 0.1125 | 8.0 | 510 | 0.1007 | 0.9614 | 0.9365 | 0.9717 | 0.9519 |
| 0.1076 | 8.99 | 573 | 0.0900 | 0.9691 | 0.9482 | 0.9770 | 0.9612 |
| 0.1188 | 9.88 | 630 | 0.1064 | 0.9622 | 0.9377 | 0.9723 | 0.9530 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2