---
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- f1
model-index:
- name: vit_flyswot_test
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.849172221610369
---

<!-- 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. -->

# vit_flyswot_test

This model is a fine-tuned version of [](https://huggingface.co/) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4777
- F1: 0.8492

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 52   | 1.2007          | 0.3533 |
| No log        | 2.0   | 104  | 1.0037          | 0.5525 |
| No log        | 3.0   | 156  | 0.8301          | 0.6318 |
| No log        | 4.0   | 208  | 0.7224          | 0.6946 |
| No log        | 5.0   | 260  | 0.7298          | 0.7145 |
| No log        | 6.0   | 312  | 0.6328          | 0.7729 |
| No log        | 7.0   | 364  | 0.6010          | 0.7992 |
| No log        | 8.0   | 416  | 0.5174          | 0.8364 |
| No log        | 9.0   | 468  | 0.5084          | 0.8479 |
| 0.6372        | 10.0  | 520  | 0.4777          | 0.8492 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6