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# resnet-101-finetuned_resnet101-adam-optimizer5e-4-autotags

This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2477
- Accuracy: 0.9267

## 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: 0.0005
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6033        | 0.99  | 65   | 2.5693          | 0.1381   |
| 1.5517        | 1.99  | 130  | 1.1376          | 0.6733   |
| 0.9423        | 2.99  | 195  | 0.6290          | 0.7895   |
| 0.6334        | 3.99  | 260  | 0.4372          | 0.86     |
| 0.4735        | 4.99  | 325  | 0.4719          | 0.8429   |
| 0.4573        | 5.99  | 390  | 0.3909          | 0.8590   |
| 0.3236        | 6.99  | 455  | 0.3507          | 0.8752   |
| 0.2511        | 7.99  | 520  | 0.2931          | 0.9019   |
| 0.2073        | 8.99  | 585  | 0.2757          | 0.9133   |
| 0.2174        | 9.99  | 650  | 0.2706          | 0.9114   |
| 0.1558        | 10.99 | 715  | 0.2654          | 0.9114   |
| 0.2017        | 11.99 | 780  | 0.2820          | 0.9114   |
| 0.134         | 12.99 | 845  | 0.2431          | 0.9238   |
| 0.0943        | 13.99 | 910  | 0.2606          | 0.9105   |
| 0.1396        | 14.99 | 975  | 0.2514          | 0.9229   |
| 0.1374        | 15.99 | 1040 | 0.2349          | 0.9305   |
| 0.0953        | 16.99 | 1105 | 0.2502          | 0.9210   |
| 0.0742        | 17.99 | 1170 | 0.2515          | 0.9210   |
| 0.0708        | 18.99 | 1235 | 0.2437          | 0.9257   |
| 0.0619        | 19.99 | 1300 | 0.2477          | 0.9267   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2

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