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# 12-classifier-finetuned-padchest

This model is a fine-tuned version of [nickmuchi/vit-finetuned-chest-xray-pneumonia](https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9215
- F1: 0.7424

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.0498        | 1.0   | 18   | 1.9843          | 0.2451 |
| 1.9376        | 2.0   | 36   | 1.8429          | 0.2757 |
| 1.7541        | 3.0   | 54   | 1.7097          | 0.2984 |
| 1.6052        | 4.0   | 72   | 1.5666          | 0.4007 |
| 1.4372        | 5.0   | 90   | 1.4392          | 0.4857 |
| 1.3696        | 6.0   | 108  | 1.3127          | 0.4894 |
| 1.2546        | 7.0   | 126  | 1.2461          | 0.5015 |
| 1.1526        | 8.0   | 144  | 1.1999          | 0.5683 |
| 1.092         | 9.0   | 162  | 1.1166          | 0.5704 |
| 1.0166        | 10.0  | 180  | 1.0568          | 0.6253 |
| 0.9753        | 11.0  | 198  | 1.0377          | 0.6055 |
| 0.939         | 12.0  | 216  | 0.9584          | 0.6535 |
| 0.916         | 13.0  | 234  | 0.9181          | 0.7092 |
| 0.8834        | 14.0  | 252  | 0.9164          | 0.7056 |
| 0.8126        | 15.0  | 270  | 0.9044          | 0.6914 |
| 0.7936        | 16.0  | 288  | 0.8730          | 0.7387 |
| 0.805         | 17.0  | 306  | 0.8627          | 0.7222 |
| 0.7146        | 18.0  | 324  | 0.8602          | 0.7136 |
| 0.7224        | 19.0  | 342  | 0.9320          | 0.6709 |
| 0.7335        | 20.0  | 360  | 0.9246          | 0.7081 |
| 0.6566        | 21.0  | 378  | 0.8585          | 0.7321 |
| 0.6451        | 22.0  | 396  | 0.8339          | 0.7341 |
| 0.6864        | 23.0  | 414  | 0.8402          | 0.7305 |
| 0.6683        | 24.0  | 432  | 0.8399          | 0.7450 |
| 0.6256        | 25.0  | 450  | 0.8209          | 0.7503 |
| 0.6041        | 26.0  | 468  | 0.8354          | 0.7461 |
| 0.6229        | 27.0  | 486  | 0.7940          | 0.7659 |
| 0.5954        | 28.0  | 504  | 0.8654          | 0.7383 |
| 0.5866        | 29.0  | 522  | 0.8525          | 0.7321 |
| 0.5895        | 30.0  | 540  | 0.8314          | 0.7510 |
| 0.5723        | 31.0  | 558  | 0.8777          | 0.7238 |
| 0.5319        | 32.0  | 576  | 0.8369          | 0.7498 |
| 0.5307        | 33.0  | 594  | 0.8801          | 0.7181 |
| 0.5285        | 34.0  | 612  | 0.8198          | 0.7420 |
| 0.4851        | 35.0  | 630  | 0.8202          | 0.7379 |
| 0.4827        | 36.0  | 648  | 0.8372          | 0.7481 |
| 0.4985        | 37.0  | 666  | 0.8032          | 0.7505 |
| 0.4714        | 38.0  | 684  | 0.8410          | 0.7390 |
| 0.4907        | 39.0  | 702  | 0.8401          | 0.7394 |
| 0.4752        | 40.0  | 720  | 0.8979          | 0.7253 |
| 0.4604        | 41.0  | 738  | 0.8654          | 0.7276 |
| 0.4287        | 42.0  | 756  | 0.9682          | 0.7113 |
| 0.4419        | 43.0  | 774  | 0.8762          | 0.7242 |
| 0.422         | 44.0  | 792  | 0.8998          | 0.7301 |
| 0.4432        | 45.0  | 810  | 0.9363          | 0.7024 |
| 0.4178        | 46.0  | 828  | 0.8751          | 0.7404 |
| 0.3901        | 47.0  | 846  | 0.8387          | 0.7432 |
| 0.4066        | 48.0  | 864  | 0.9137          | 0.7184 |
| 0.3919        | 49.0  | 882  | 0.8873          | 0.7234 |
| 0.4027        | 50.0  | 900  | 0.8805          | 0.7358 |
| 0.3593        | 51.0  | 918  | 0.8617          | 0.7332 |
| 0.3774        | 52.0  | 936  | 0.8781          | 0.7354 |
| 0.364         | 53.0  | 954  | 0.8993          | 0.7225 |
| 0.3585        | 54.0  | 972  | 0.9047          | 0.7293 |
| 0.3539        | 55.0  | 990  | 0.8719          | 0.7462 |
| 0.3224        | 56.0  | 1008 | 0.8578          | 0.7632 |
| 0.3486        | 57.0  | 1026 | 0.8934          | 0.7384 |
| 0.3359        | 58.0  | 1044 | 0.8853          | 0.7428 |
| 0.288         | 59.0  | 1062 | 0.8655          | 0.7466 |
| 0.297         | 60.0  | 1080 | 0.8850          | 0.7394 |
| 0.2875        | 61.0  | 1098 | 0.9405          | 0.7247 |
| 0.3267        | 62.0  | 1116 | 0.9057          | 0.7222 |
| 0.2825        | 63.0  | 1134 | 0.9186          | 0.7413 |
| 0.3129        | 64.0  | 1152 | 0.9200          | 0.7409 |
| 0.3264        | 65.0  | 1170 | 0.9506          | 0.7404 |
| 0.3079        | 66.0  | 1188 | 0.9671          | 0.7176 |
| 0.2915        | 67.0  | 1206 | 0.9504          | 0.7417 |
| 0.2797        | 68.0  | 1224 | 0.9254          | 0.7424 |
| 0.2496        | 69.0  | 1242 | 0.8910          | 0.7433 |
| 0.3063        | 70.0  | 1260 | 0.9178          | 0.7292 |
| 0.2626        | 71.0  | 1278 | 0.9140          | 0.7415 |
| 0.2552        | 72.0  | 1296 | 0.9249          | 0.7333 |
| 0.2655        | 73.0  | 1314 | 0.9000          | 0.7508 |
| 0.2797        | 74.0  | 1332 | 0.8777          | 0.7400 |
| 0.2678        | 75.0  | 1350 | 0.9043          | 0.7357 |
| 0.2464        | 76.0  | 1368 | 0.9432          | 0.7258 |
| 0.2789        | 77.0  | 1386 | 0.9355          | 0.7356 |
| 0.2617        | 78.0  | 1404 | 0.9354          | 0.7333 |
| 0.2381        | 79.0  | 1422 | 0.8852          | 0.7545 |
| 0.2573        | 80.0  | 1440 | 0.9500          | 0.7384 |
| 0.2429        | 81.0  | 1458 | 0.9095          | 0.7470 |
| 0.2513        | 82.0  | 1476 | 0.9898          | 0.7272 |
| 0.2422        | 83.0  | 1494 | 0.9237          | 0.7487 |
| 0.2476        | 84.0  | 1512 | 0.9146          | 0.7505 |
| 0.2399        | 85.0  | 1530 | 0.9386          | 0.7345 |
| 0.2343        | 86.0  | 1548 | 0.9082          | 0.7414 |
| 0.2336        | 87.0  | 1566 | 0.9074          | 0.7491 |
| 0.2176        | 88.0  | 1584 | 0.9291          | 0.7359 |
| 0.2253        | 89.0  | 1602 | 0.9334          | 0.7331 |
| 0.2244        | 90.0  | 1620 | 0.9364          | 0.7412 |
| 0.2215        | 91.0  | 1638 | 0.9617          | 0.7269 |
| 0.2049        | 92.0  | 1656 | 0.9155          | 0.7562 |
| 0.2238        | 93.0  | 1674 | 0.9206          | 0.7517 |
| 0.1761        | 94.0  | 1692 | 0.9312          | 0.7402 |
| 0.2025        | 95.0  | 1710 | 0.9287          | 0.7444 |
| 0.214         | 96.0  | 1728 | 0.9215          | 0.7444 |
| 0.2493        | 97.0  | 1746 | 0.9268          | 0.7489 |
| 0.2414        | 98.0  | 1764 | 0.9190          | 0.7477 |
| 0.1971        | 99.0  | 1782 | 0.9221          | 0.7451 |
| 0.2015        | 100.0 | 1800 | 0.9215          | 0.7424 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.19.0
- Tokenizers 0.12.1

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