
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# resnet-18-dungeons-001

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: 1.1886
- Accuracy: 0.5

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 85
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.0594        | 6.6667  | 10   | 1.3086          | 0.5833   |
| 0.0973        | 13.3333 | 20   | 1.3523          | 0.5      |
| 0.068         | 20.0    | 30   | 1.2428          | 0.5833   |
| 0.0671        | 26.6667 | 40   | 1.2280          | 0.5833   |
| 0.0527        | 33.3333 | 50   | 1.2677          | 0.5833   |
| 0.0592        | 40.0    | 60   | 1.2846          | 0.5833   |
| 0.0446        | 46.6667 | 70   | 1.2210          | 0.5833   |
| 0.0565        | 53.3333 | 80   | 1.1886          | 0.5      |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1

five four one three twelve two zero