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image-multi-class-classification-not-evaluated

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image-multi-class-classification-not-evaluated
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mnist
- autoevaluate/mnist-sample
metrics:
- accuracy
duplicated_from: autoevaluate/image-multi-class-classification
model-index:
- name: autoevaluate/image-multi-class-classification-not-evaluated
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: autoevaluate/mnist-sample
      type: autoevaluate/mnist-sample
      config: autoevaluate--mnist-sample
      split: test
    metrics:
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    - type: f1
      value: 0.9496869212452598
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      verified: true
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    - type: precision
      value: 0.9478535353535353
      name: Precision Macro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzU2NTgzMDM5ZGNjMjY2YTEyM2MxNDc4MGExYmEyMzFhYjc1ZGI1OTU3ZmI5N2Q1NzIxNmM4YWM2YjA3MzJjYSIsInZlcnNpb24iOjF9.IkFI2xMoiYSuBrg4rI99d72CdCqbllBHLb2mkBxwFePS7QVa-iu5uioEUt5eLvLIh_WeC_H4PR8RX8EJpN06Cg
    - type: precision
      value: 0.95
      name: Precision Micro
      verified: true
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    - type: precision
      value: 0.9510353535353535
      name: Precision Weighted
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTY3ZGMzMzA4N2Y1NTM0NDBlYzZiNzNhZDBhNDhiNDJjMDg1NmU1OTEyOWRhOTEzYmY0OTNlYjEyYWNkMDhlMiIsInZlcnNpb24iOjF9.qlUvJj53M6miiYj_WRSzM4Dba8zT1ccBbZ7o__O_MZy3i2orc1Bug7A8Jl0xm2jYZ-t5DQtPbucZ6KOlcrF9Cg
    - type: recall
      value: 0.9530555555555555
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      verified: true
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    - type: recall
      value: 0.95
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      verified: true
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    - type: recall
      value: 0.95
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      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmFjNjYyNmJmZjk0ZWZlZjZlODc0NDJjYjI1OTk0NTQ3NzdiOTY1ZmQ0MjVmODRjN2M5NzUyNGEwMWMwMTRlNSIsInZlcnNpb24iOjF9.qSk10iM348bjetzTla7MqbVcxyo5TpcIWoJR5N-HE5tiZ0mFwJ5RuL0YqSL_M_kgLdfb5TucnvoC_D6vDri8BA
    - type: loss
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      name: loss
      verified: true
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---

<!-- 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. -->

# image-classification

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the mnist dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0556
- Accuracy: 0.9833

## 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3743        | 1.0   | 422  | 0.0556          | 0.9833   |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1