---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: facebook/deit-base-patch16-224
model-index:
- name: chest-deit-base-finetuned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# chest-deit-base-finetuned

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0979
- Accuracy: 0.9622
- Precision: 0.9531
- Recall: 0.9562
- F1: 0.9546

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2556        | 0.99  | 63   | 0.2019          | 0.9185   | 0.9446    | 0.8469 | 0.8822 |
| 0.2302        | 1.99  | 127  | 0.1098          | 0.9614   | 0.9396    | 0.9654 | 0.9514 |
| 0.2258        | 3.0   | 191  | 0.1151          | 0.9622   | 0.9641    | 0.9372 | 0.9496 |
| 0.1465        | 4.0   | 255  | 0.0733          | 0.9725   | 0.9653    | 0.9633 | 0.9643 |
| 0.1763        | 4.99  | 318  | 0.0763          | 0.9725   | 0.9703    | 0.9580 | 0.9639 |
| 0.1627        | 5.99  | 382  | 0.1057          | 0.9571   | 0.9315    | 0.9656 | 0.9466 |
| 0.1509        | 7.0   | 446  | 0.0701          | 0.9751   | 0.9638    | 0.9725 | 0.9680 |
| 0.1209        | 8.0   | 510  | 0.1047          | 0.9571   | 0.9315    | 0.9656 | 0.9466 |
| 0.0961        | 8.99  | 573  | 0.0721          | 0.9734   | 0.9577    | 0.9756 | 0.9662 |
| 0.1063        | 9.88  | 630  | 0.0885          | 0.9622   | 0.9398    | 0.9681 | 0.9526 |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2