---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
model-index:
- name: chest-beit-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-beit-base-finetuned

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2620
- Accuracy: 0.9107
- Precision: 0.8923
- Recall: 0.8923
- F1: 0.8923

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4775        | 0.99  | 63   | 0.2264          | 0.9142   | 0.8850    | 0.8962 | 0.8903 |
| 0.7117        | 1.99  | 127  | 0.4008          | 0.7391   | 0.3695    | 0.5    | 0.4250 |
| 0.4115        | 3.0   | 191  | 0.4358          | 0.8155   | 0.7871    | 0.8645 | 0.7957 |
| 0.3631        | 4.0   | 255  | 0.3091          | 0.8798   | 0.8381    | 0.8708 | 0.8518 |
| 0.3794        | 4.99  | 318  | 0.2802          | 0.8798   | 0.8393    | 0.8623 | 0.8495 |
| 0.3713        | 5.99  | 382  | 0.2805          | 0.8773   | 0.8371    | 0.8542 | 0.8449 |
| 0.3953        | 7.0   | 446  | 0.3397          | 0.8584   | 0.8185    | 0.8872 | 0.8367 |
| 0.3218        | 8.0   | 510  | 0.3072          | 0.8670   | 0.8257    | 0.8898 | 0.8448 |
| 0.3219        | 8.99  | 573  | 0.2633          | 0.8961   | 0.8582    | 0.8872 | 0.8708 |
| 0.3049        | 9.88  | 630  | 0.2739          | 0.8927   | 0.8528    | 0.8912 | 0.8685 |


### Framework versions

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