metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: chest-vit-base-finetuned
results: []
chest-vit-base-finetuned
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0982
- Accuracy: 0.9639
- Precision: 0.9419
- Recall: 0.9703
- F1: 0.9548
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 |
|---|---|---|---|---|---|---|---|
| 0.211 | 0.99 | 63 | 0.1140 | 0.9605 | 0.9401 | 0.9616 | 0.9501 |
| 0.1911 | 1.99 | 127 | 0.1517 | 0.9330 | 0.8989 | 0.9483 | 0.9186 |
| 0.1695 | 3.0 | 191 | 0.1163 | 0.9579 | 0.9354 | 0.9609 | 0.9471 |
| 0.1556 | 4.0 | 255 | 0.1159 | 0.9571 | 0.9669 | 0.9220 | 0.9417 |
| 0.173 | 4.99 | 318 | 0.1166 | 0.9502 | 0.9229 | 0.9578 | 0.9381 |
| 0.1485 | 5.99 | 382 | 0.0825 | 0.9717 | 0.9578 | 0.9702 | 0.9638 |
| 0.1854 | 7.0 | 446 | 0.0878 | 0.9717 | 0.9578 | 0.9702 | 0.9638 |
| 0.1353 | 8.0 | 510 | 0.1060 | 0.9588 | 0.9351 | 0.9647 | 0.9484 |
| 0.1196 | 8.99 | 573 | 0.0882 | 0.9691 | 0.9527 | 0.9695 | 0.9607 |
| 0.1218 | 9.88 | 630 | 0.0982 | 0.9639 | 0.9419 | 0.9703 | 0.9548 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2