pytorch vit image-classification dataset:image_folder transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- f1
model-index:
- name: deit_flyswot
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.990761405263678
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deit_flyswot

This model was trained from scratch on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0755
- F1: 0.9908

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 666
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 52   | 0.5710          | 0.8095 |
| No log        | 2.0   | 104  | 0.2814          | 0.9380 |
| No log        | 3.0   | 156  | 0.1719          | 0.9555 |
| No log        | 4.0   | 208  | 0.1410          | 0.9692 |
| No log        | 5.0   | 260  | 0.1457          | 0.9680 |
| No log        | 6.0   | 312  | 0.1084          | 0.9747 |
| No log        | 7.0   | 364  | 0.0892          | 0.9736 |
| No log        | 8.0   | 416  | 0.0962          | 0.9831 |
| No log        | 9.0   | 468  | 0.0819          | 0.9796 |
| 0.2034        | 10.0  | 520  | 0.0916          | 0.9778 |
| 0.2034        | 11.0  | 572  | 0.0793          | 0.9827 |
| 0.2034        | 12.0  | 624  | 0.0818          | 0.9894 |
| 0.2034        | 13.0  | 676  | 0.0852          | 0.9807 |
| 0.2034        | 14.0  | 728  | 0.0938          | 0.9778 |
| 0.2034        | 15.0  | 780  | 0.0814          | 0.9876 |
| 0.2034        | 16.0  | 832  | 0.0702          | 0.9892 |
| 0.2034        | 17.0  | 884  | 0.0801          | 0.9892 |
| 0.2034        | 18.0  | 936  | 0.0806          | 0.9892 |
| 0.2034        | 19.0  | 988  | 0.0769          | 0.9926 |
| 0.0115        | 20.0  | 1040 | 0.0800          | 0.9926 |
| 0.0115        | 21.0  | 1092 | 0.0794          | 0.9926 |
| 0.0115        | 22.0  | 1144 | 0.0762          | 0.9846 |
| 0.0115        | 23.0  | 1196 | 0.0789          | 0.9830 |
| 0.0115        | 24.0  | 1248 | 0.0794          | 0.9829 |
| 0.0115        | 25.0  | 1300 | 0.0770          | 0.9908 |
| 0.0115        | 26.0  | 1352 | 0.0791          | 0.9829 |
| 0.0115        | 27.0  | 1404 | 0.0813          | 0.9892 |
| 0.0115        | 28.0  | 1456 | 0.0816          | 0.9908 |
| 0.0058        | 29.0  | 1508 | 0.0774          | 0.9908 |
| 0.0058        | 30.0  | 1560 | 0.0755          | 0.9908 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
