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# convnext-tiny-224_flyswot

This model was trained from scratch on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5319
- F1: 0.9756

## 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: 50
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 52   | 0.5478          | 0.9720 |
| No log        | 2.0   | 104  | 0.5432          | 0.9709 |
| No log        | 3.0   | 156  | 0.5437          | 0.9731 |
| No log        | 4.0   | 208  | 0.5433          | 0.9712 |
| No log        | 5.0   | 260  | 0.5373          | 0.9745 |
| No log        | 6.0   | 312  | 0.5371          | 0.9756 |
| No log        | 7.0   | 364  | 0.5381          | 0.9737 |
| No log        | 8.0   | 416  | 0.5376          | 0.9744 |
| No log        | 9.0   | 468  | 0.5431          | 0.9694 |
| 0.4761        | 10.0  | 520  | 0.5468          | 0.9725 |
| 0.4761        | 11.0  | 572  | 0.5404          | 0.9755 |
| 0.4761        | 12.0  | 624  | 0.5481          | 0.9669 |
| 0.4761        | 13.0  | 676  | 0.5432          | 0.9687 |
| 0.4761        | 14.0  | 728  | 0.5409          | 0.9731 |
| 0.4761        | 15.0  | 780  | 0.5403          | 0.9737 |
| 0.4761        | 16.0  | 832  | 0.5393          | 0.9737 |
| 0.4761        | 17.0  | 884  | 0.5412          | 0.9719 |
| 0.4761        | 18.0  | 936  | 0.5433          | 0.9674 |
| 0.4761        | 19.0  | 988  | 0.5367          | 0.9755 |
| 0.4705        | 20.0  | 1040 | 0.5389          | 0.9737 |
| 0.4705        | 21.0  | 1092 | 0.5396          | 0.9737 |
| 0.4705        | 22.0  | 1144 | 0.5514          | 0.9683 |
| 0.4705        | 23.0  | 1196 | 0.5550          | 0.9617 |
| 0.4705        | 24.0  | 1248 | 0.5428          | 0.9719 |
| 0.4705        | 25.0  | 1300 | 0.5371          | 0.9719 |
| 0.4705        | 26.0  | 1352 | 0.5455          | 0.9719 |
| 0.4705        | 27.0  | 1404 | 0.5409          | 0.9680 |
| 0.4705        | 28.0  | 1456 | 0.5345          | 0.9756 |
| 0.4696        | 29.0  | 1508 | 0.5381          | 0.9756 |
| 0.4696        | 30.0  | 1560 | 0.5387          | 0.9705 |
| 0.4696        | 31.0  | 1612 | 0.5540          | 0.9605 |
| 0.4696        | 32.0  | 1664 | 0.5467          | 0.9706 |
| 0.4696        | 33.0  | 1716 | 0.5322          | 0.9756 |
| 0.4696        | 34.0  | 1768 | 0.5325          | 0.9756 |
| 0.4696        | 35.0  | 1820 | 0.5305          | 0.9737 |
| 0.4696        | 36.0  | 1872 | 0.5305          | 0.9769 |
| 0.4696        | 37.0  | 1924 | 0.5345          | 0.9756 |
| 0.4696        | 38.0  | 1976 | 0.5315          | 0.9737 |
| 0.4699        | 39.0  | 2028 | 0.5333          | 0.9756 |
| 0.4699        | 40.0  | 2080 | 0.5316          | 0.9756 |
| 0.4699        | 41.0  | 2132 | 0.5284          | 0.9756 |
| 0.4699        | 42.0  | 2184 | 0.5325          | 0.9756 |
| 0.4699        | 43.0  | 2236 | 0.5321          | 0.9756 |
| 0.4699        | 44.0  | 2288 | 0.5322          | 0.9756 |
| 0.4699        | 45.0  | 2340 | 0.5323          | 0.9756 |
| 0.4699        | 46.0  | 2392 | 0.5318          | 0.9756 |
| 0.4699        | 47.0  | 2444 | 0.5329          | 0.9756 |
| 0.4699        | 48.0  | 2496 | 0.5317          | 0.9756 |
| 0.4701        | 49.0  | 2548 | 0.5317          | 0.9756 |
| 0.4701        | 50.0  | 2600 | 0.5319          | 0.9756 |


### Framework versions

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

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