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# 10-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: 0.2197
- F1: 0.9062

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7175        | 1.0   | 18   | 0.6978          | 0.5508 |
| 0.6996        | 2.0   | 36   | 0.6699          | 0.7605 |
| 0.659         | 3.0   | 54   | 0.6291          | 0.8044 |
| 0.5937        | 4.0   | 72   | 0.5778          | 0.7920 |
| 0.5124        | 5.0   | 90   | 0.5113          | 0.7934 |
| 0.4668        | 6.0   | 108  | 0.4066          | 0.7934 |
| 0.4079        | 7.0   | 126  | 0.4105          | 0.7934 |
| 0.363         | 8.0   | 144  | 0.3652          | 0.7934 |
| 0.337         | 9.0   | 162  | 0.3410          | 0.7934 |
| 0.3172        | 10.0  | 180  | 0.3272          | 0.7934 |
| 0.3082        | 11.0  | 198  | 0.2930          | 0.7934 |
| 0.2967        | 12.0  | 216  | 0.2814          | 0.7934 |
| 0.2889        | 13.0  | 234  | 0.2665          | 0.7934 |
| 0.2636        | 14.0  | 252  | 0.2846          | 0.7934 |
| 0.2694        | 15.0  | 270  | 0.2610          | 0.7934 |
| 0.2663        | 16.0  | 288  | 0.2828          | 0.7934 |
| 0.2573        | 17.0  | 306  | 0.2615          | 0.7934 |
| 0.2558        | 18.0  | 324  | 0.2606          | 0.7934 |
| 0.2492        | 19.0  | 342  | 0.2532          | 0.7934 |
| 0.2513        | 20.0  | 360  | 0.2559          | 0.7934 |
| 0.2429        | 21.0  | 378  | 0.2497          | 0.7934 |
| 0.2361        | 22.0  | 396  | 0.2412          | 0.7934 |
| 0.2423        | 23.0  | 414  | 0.2494          | 0.8235 |
| 0.2479        | 24.0  | 432  | 0.2446          | 0.8290 |
| 0.2237        | 25.0  | 450  | 0.2425          | 0.8428 |
| 0.2282        | 26.0  | 468  | 0.2446          | 0.8573 |
| 0.2343        | 27.0  | 486  | 0.2348          | 0.8344 |
| 0.2169        | 28.0  | 504  | 0.2358          | 0.8547 |
| 0.2169        | 29.0  | 522  | 0.2400          | 0.8622 |
| 0.2341        | 30.0  | 540  | 0.2342          | 0.8579 |
| 0.2241        | 31.0  | 558  | 0.2266          | 0.8511 |
| 0.2132        | 32.0  | 576  | 0.2250          | 0.8662 |
| 0.2155        | 33.0  | 594  | 0.2222          | 0.8485 |
| 0.2014        | 34.0  | 612  | 0.2279          | 0.8659 |
| 0.2033        | 35.0  | 630  | 0.2296          | 0.8886 |
| 0.1993        | 36.0  | 648  | 0.2252          | 0.8909 |
| 0.228         | 37.0  | 666  | 0.2226          | 0.8742 |
| 0.2292        | 38.0  | 684  | 0.2274          | 0.9030 |
| 0.202         | 39.0  | 702  | 0.2307          | 0.8997 |
| 0.2133        | 40.0  | 720  | 0.2244          | 0.8977 |
| 0.214         | 41.0  | 738  | 0.2281          | 0.9053 |
| 0.2203        | 42.0  | 756  | 0.2251          | 0.9020 |
| 0.2071        | 43.0  | 774  | 0.2214          | 0.8848 |
| 0.2125        | 44.0  | 792  | 0.2196          | 0.8932 |
| 0.2137        | 45.0  | 810  | 0.2187          | 0.8811 |
| 0.2073        | 46.0  | 828  | 0.2183          | 0.9020 |
| 0.2119        | 47.0  | 846  | 0.2185          | 0.9109 |
| 0.2018        | 48.0  | 864  | 0.2199          | 0.8943 |
| 0.1971        | 49.0  | 882  | 0.2211          | 0.9053 |
| 0.2079        | 50.0  | 900  | 0.2197          | 0.9062 |


### Framework versions

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

artifacts no artifacts