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# 11-classifier-finetuned-padchest

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1743
- F1: 0.5098

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.0747        | 1.0   | 18   | 2.0666          | 0.1549 |
| 2.0661        | 2.0   | 36   | 2.0560          | 0.1777 |
| 2.0497        | 3.0   | 54   | 2.0385          | 0.2169 |
| 2.018         | 4.0   | 72   | 2.0047          | 0.2515 |
| 1.9792        | 5.0   | 90   | 1.9773          | 0.2329 |
| 1.9619        | 6.0   | 108  | 1.9421          | 0.2321 |
| 1.9186        | 7.0   | 126  | 1.9145          | 0.2055 |
| 1.8838        | 8.0   | 144  | 1.8976          | 0.2596 |
| 1.8402        | 9.0   | 162  | 1.8444          | 0.2337 |
| 1.7906        | 10.0  | 180  | 1.7951          | 0.2397 |
| 1.7716        | 11.0  | 198  | 1.7695          | 0.3373 |
| 1.7474        | 12.0  | 216  | 1.7940          | 0.3209 |
| 1.6957        | 13.0  | 234  | 1.7425          | 0.3314 |
| 1.6791        | 14.0  | 252  | 1.6727          | 0.3558 |
| 1.6483        | 15.0  | 270  | 1.6638          | 0.3895 |
| 1.614         | 16.0  | 288  | 1.6513          | 0.4186 |
| 1.6166        | 17.0  | 306  | 1.6002          | 0.4406 |
| 1.5654        | 18.0  | 324  | 1.5528          | 0.4627 |
| 1.5145        | 19.0  | 342  | 1.5571          | 0.4676 |
| 1.5049        | 20.0  | 360  | 1.4334          | 0.4364 |
| 1.457         | 21.0  | 378  | 1.4711          | 0.4535 |
| 1.4516        | 22.0  | 396  | 1.5013          | 0.4516 |
| 1.4172        | 23.0  | 414  | 1.3614          | 0.4682 |
| 1.3817        | 24.0  | 432  | 1.3519          | 0.4545 |
| 1.3987        | 25.0  | 450  | 1.3806          | 0.4759 |
| 1.4063        | 26.0  | 468  | 1.2961          | 0.4866 |
| 1.3684        | 27.0  | 486  | 1.3328          | 0.4768 |
| 1.3789        | 28.0  | 504  | 1.2810          | 0.4859 |
| 1.341         | 29.0  | 522  | 1.3227          | 0.4737 |
| 1.3574        | 30.0  | 540  | 1.2406          | 0.5025 |
| 1.357         | 31.0  | 558  | 1.2427          | 0.5033 |
| 1.3204        | 32.0  | 576  | 1.2478          | 0.5053 |
| 1.3122        | 33.0  | 594  | 1.2205          | 0.5133 |
| 1.334         | 34.0  | 612  | 1.2138          | 0.5204 |
| 1.2998        | 35.0  | 630  | 1.2122          | 0.5111 |
| 1.3097        | 36.0  | 648  | 1.2118          | 0.5102 |
| 1.2956        | 37.0  | 666  | 1.2077          | 0.5163 |
| 1.3058        | 38.0  | 684  | 1.2023          | 0.5157 |
| 1.2851        | 39.0  | 702  | 1.1968          | 0.5067 |
| 1.2728        | 40.0  | 720  | 1.1940          | 0.5169 |
| 1.2653        | 41.0  | 738  | 1.1700          | 0.5165 |
| 1.2837        | 42.0  | 756  | 1.1767          | 0.5262 |
| 1.2789        | 43.0  | 774  | 1.1885          | 0.5146 |
| 1.2343        | 44.0  | 792  | 1.1925          | 0.5101 |
| 1.2454        | 45.0  | 810  | 1.1874          | 0.5119 |
| 1.2922        | 46.0  | 828  | 1.1845          | 0.5216 |
| 1.2547        | 47.0  | 846  | 1.1920          | 0.5299 |
| 1.272         | 48.0  | 864  | 1.1732          | 0.5225 |
| 1.2506        | 49.0  | 882  | 1.1722          | 0.5117 |
| 1.2494        | 50.0  | 900  | 1.1743          | 0.5098 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3

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