---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-finetuned-gardner-exp-max
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8355704697986577
---

<!-- 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. -->

# swinv2-tiny-patch4-window8-256-finetuned-gardner-exp-max

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5500
- Accuracy: 0.8356

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6043        | 0.97  | 14   | 1.5288          | 0.5415   |
| 1.4967        | 2.0   | 29   | 1.1719          | 0.5415   |
| 1.1276        | 2.97  | 43   | 1.0525          | 0.5463   |
| 1.0796        | 4.0   | 58   | 0.9086          | 0.6537   |
| 0.9387        | 4.97  | 72   | 0.8500          | 0.6439   |
| 0.9232        | 6.0   | 87   | 0.8190          | 0.6732   |
| 0.8456        | 6.97  | 101  | 0.8042          | 0.6878   |
| 0.8348        | 8.0   | 116  | 0.7770          | 0.6927   |
| 0.8057        | 8.97  | 130  | 0.7457          | 0.7073   |
| 0.8033        | 10.0  | 145  | 0.7353          | 0.7024   |
| 0.7822        | 10.97 | 159  | 0.7166          | 0.7122   |
| 0.7594        | 12.0  | 174  | 0.7188          | 0.7171   |
| 0.7777        | 12.97 | 188  | 0.7086          | 0.7171   |
| 0.7445        | 14.0  | 203  | 0.7139          | 0.6878   |
| 0.7513        | 14.48 | 210  | 0.7139          | 0.6878   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0