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# resnet-18

This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 11425938732811038938338101821440.0000
- Accuracy: 0.2857

## 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: 3

### Training results

| Training Loss                         | Epoch  | Step | Validation Loss                       | Accuracy |
|:-------------------------------------:|:------:|:----:|:-------------------------------------:|:--------:|
| No log                                | 0.9091 | 5    | 11425938732811038938338101821440.0000 | 0.2857   |
| 10876880651531499783855888400384.0000 | 2.0    | 11   | 11425938732811038938338101821440.0000 | 0.2857   |
| 10876880651531499783855888400384.0000 | 2.7273 | 15   | 11425938732811038938338101821440.0000 | 0.2857   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

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