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# resnet-101-finetuned-CivilEng11k-newDS

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: 0.4541
- Accuracy: 0.9932

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 20
- total_train_batch_size: 640
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.54  | 1    | 1.0986          | 0.4136   |
| No log        | 1.62  | 3    | 1.0295          | 0.4339   |
| No log        | 2.7   | 5    | 0.8537          | 0.4339   |
| No log        | 3.78  | 7    | 0.6785          | 0.4441   |
| No log        | 4.86  | 9    | 0.6141          | 0.6576   |
| No log        | 5.95  | 11   | 0.5794          | 0.7559   |
| No log        | 6.49  | 12   | 0.5616          | 0.8034   |
| No log        | 7.57  | 14   | 0.5304          | 0.8475   |
| No log        | 8.65  | 16   | 0.4964          | 0.9492   |
| No log        | 9.73  | 18   | 0.4680          | 0.9864   |
| 0.6919        | 10.81 | 20   | 0.4541          | 0.9932   |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1
- Datasets 2.18.0
- Tokenizers 0.15.1

crazing live_knot steel_defect