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# models

This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4704
- Accuracy: 0.8182

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4144        | 0.99  | 20   | 0.9938          | 0.7      |
| 0.7896        | 1.98  | 40   | 0.7022          | 0.7152   |
| 0.6191        | 2.96  | 60   | 0.6079          | 0.7636   |
| 0.6114        | 4.0   | 81   | 0.5554          | 0.7939   |
| 0.5365        | 4.99  | 101  | 0.5233          | 0.8152   |
| 0.4989        | 5.98  | 121  | 0.4934          | 0.8303   |
| 0.5111        | 6.96  | 141  | 0.5181          | 0.8      |
| 0.476         | 8.0   | 162  | 0.4844          | 0.8182   |
| 0.4655        | 8.99  | 182  | 0.4870          | 0.8152   |
| 0.4335        | 9.98  | 202  | 0.4802          | 0.8242   |
| 0.44          | 10.96 | 222  | 0.4776          | 0.8182   |
| 0.3989        | 12.0  | 243  | 0.4804          | 0.8182   |
| 0.4007        | 12.99 | 263  | 0.4768          | 0.8242   |
| 0.3987        | 13.98 | 283  | 0.4610          | 0.8303   |
| 0.3922        | 14.96 | 303  | 0.4578          | 0.8212   |
| 0.3924        | 16.0  | 324  | 0.4804          | 0.8182   |
| 0.3995        | 16.99 | 344  | 0.4736          | 0.8121   |
| 0.3623        | 17.98 | 364  | 0.4715          | 0.8121   |
| 0.3621        | 18.96 | 384  | 0.4671          | 0.8212   |
| 0.3629        | 19.75 | 400  | 0.4704          | 0.8182   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3

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