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# convnext_flyswot

This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1441
- F1: 0.9592

## 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   | 0.6833          | 0.7484 |
| No log        | 2.0   | 104  | 0.3666          | 0.8750 |
| No log        | 3.0   | 156  | 0.2090          | 0.9321 |
| No log        | 4.0   | 208  | 0.1478          | 0.9449 |
| No log        | 5.0   | 260  | 0.1002          | 0.9518 |
| No log        | 6.0   | 312  | 0.1053          | 0.9506 |
| No log        | 7.0   | 364  | 0.1182          | 0.9616 |
| No log        | 8.0   | 416  | 0.1102          | 0.9592 |
| No log        | 9.0   | 468  | 0.1262          | 0.9616 |
| 0.203         | 10.0  | 520  | 0.1286          | 0.9616 |
| 0.203         | 11.0  | 572  | 0.1355          | 0.9592 |
| 0.203         | 12.0  | 624  | 0.1299          | 0.9592 |
| 0.203         | 13.0  | 676  | 0.1154          | 0.9592 |
| 0.203         | 14.0  | 728  | 0.1385          | 0.9580 |
| 0.203         | 15.0  | 780  | 0.1330          | 0.9592 |
| 0.203         | 16.0  | 832  | 0.1390          | 0.9592 |
| 0.203         | 17.0  | 884  | 0.1386          | 0.9592 |
| 0.203         | 18.0  | 936  | 0.1390          | 0.9592 |
| 0.203         | 19.0  | 988  | 0.1409          | 0.9592 |
| 0.0006        | 20.0  | 1040 | 0.1411          | 0.9592 |
| 0.0006        | 21.0  | 1092 | 0.1413          | 0.9592 |
| 0.0006        | 22.0  | 1144 | 0.1415          | 0.9592 |
| 0.0006        | 23.0  | 1196 | 0.1426          | 0.9592 |
| 0.0006        | 24.0  | 1248 | 0.1435          | 0.9592 |
| 0.0006        | 25.0  | 1300 | 0.1438          | 0.9592 |
| 0.0006        | 26.0  | 1352 | 0.1434          | 0.9592 |
| 0.0006        | 27.0  | 1404 | 0.1437          | 0.9592 |
| 0.0006        | 28.0  | 1456 | 0.1441          | 0.9592 |
| 0.0002        | 29.0  | 1508 | 0.1440          | 0.9592 |
| 0.0002        | 30.0  | 1560 | 0.1441          | 0.9592 |


### Framework versions

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

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