transformers tensorboard safetensors swin image-classification generated_from_trainer dataset:imagefolder base_model:victor/autotrain-donut-vs-croissant-1417653460 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: victor/autotrain-donut-vs-croissant-1417653460
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: donat-croissant
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.988950276243094
---

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# donat-croissant

This model is a fine-tuned version of [victor/autotrain-donut-vs-croissant-1417653460](https://huggingface.co/victor/autotrain-donut-vs-croissant-1417653460) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0189
- Accuracy: 0.9890

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
