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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- image_folder |
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metrics: |
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- f1 |
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model-index: |
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- name: convnext-tiny-224_flyswot |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: image_folder |
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type: image_folder |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.9756290792360154 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# convnext-tiny-224_flyswot |
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This model was trained from scratch on the image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5319 |
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- F1: 0.9756 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 666 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 52 | 0.5478 | 0.9720 | |
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| No log | 2.0 | 104 | 0.5432 | 0.9709 | |
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| No log | 3.0 | 156 | 0.5437 | 0.9731 | |
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| No log | 4.0 | 208 | 0.5433 | 0.9712 | |
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| No log | 5.0 | 260 | 0.5373 | 0.9745 | |
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| No log | 6.0 | 312 | 0.5371 | 0.9756 | |
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| No log | 7.0 | 364 | 0.5381 | 0.9737 | |
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| No log | 8.0 | 416 | 0.5376 | 0.9744 | |
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| No log | 9.0 | 468 | 0.5431 | 0.9694 | |
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| 0.4761 | 10.0 | 520 | 0.5468 | 0.9725 | |
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| 0.4761 | 11.0 | 572 | 0.5404 | 0.9755 | |
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| 0.4761 | 12.0 | 624 | 0.5481 | 0.9669 | |
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| 0.4761 | 13.0 | 676 | 0.5432 | 0.9687 | |
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| 0.4761 | 14.0 | 728 | 0.5409 | 0.9731 | |
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| 0.4761 | 15.0 | 780 | 0.5403 | 0.9737 | |
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| 0.4761 | 16.0 | 832 | 0.5393 | 0.9737 | |
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| 0.4761 | 17.0 | 884 | 0.5412 | 0.9719 | |
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| 0.4761 | 18.0 | 936 | 0.5433 | 0.9674 | |
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| 0.4761 | 19.0 | 988 | 0.5367 | 0.9755 | |
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| 0.4705 | 20.0 | 1040 | 0.5389 | 0.9737 | |
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| 0.4705 | 21.0 | 1092 | 0.5396 | 0.9737 | |
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| 0.4705 | 22.0 | 1144 | 0.5514 | 0.9683 | |
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| 0.4705 | 23.0 | 1196 | 0.5550 | 0.9617 | |
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| 0.4705 | 24.0 | 1248 | 0.5428 | 0.9719 | |
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| 0.4705 | 25.0 | 1300 | 0.5371 | 0.9719 | |
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| 0.4705 | 26.0 | 1352 | 0.5455 | 0.9719 | |
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| 0.4705 | 27.0 | 1404 | 0.5409 | 0.9680 | |
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| 0.4705 | 28.0 | 1456 | 0.5345 | 0.9756 | |
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| 0.4696 | 29.0 | 1508 | 0.5381 | 0.9756 | |
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| 0.4696 | 30.0 | 1560 | 0.5387 | 0.9705 | |
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| 0.4696 | 31.0 | 1612 | 0.5540 | 0.9605 | |
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| 0.4696 | 32.0 | 1664 | 0.5467 | 0.9706 | |
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| 0.4696 | 33.0 | 1716 | 0.5322 | 0.9756 | |
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| 0.4696 | 34.0 | 1768 | 0.5325 | 0.9756 | |
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| 0.4696 | 35.0 | 1820 | 0.5305 | 0.9737 | |
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| 0.4696 | 36.0 | 1872 | 0.5305 | 0.9769 | |
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| 0.4696 | 37.0 | 1924 | 0.5345 | 0.9756 | |
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| 0.4696 | 38.0 | 1976 | 0.5315 | 0.9737 | |
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| 0.4699 | 39.0 | 2028 | 0.5333 | 0.9756 | |
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| 0.4699 | 40.0 | 2080 | 0.5316 | 0.9756 | |
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| 0.4699 | 41.0 | 2132 | 0.5284 | 0.9756 | |
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| 0.4699 | 42.0 | 2184 | 0.5325 | 0.9756 | |
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| 0.4699 | 43.0 | 2236 | 0.5321 | 0.9756 | |
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| 0.4699 | 44.0 | 2288 | 0.5322 | 0.9756 | |
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| 0.4699 | 45.0 | 2340 | 0.5323 | 0.9756 | |
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| 0.4699 | 46.0 | 2392 | 0.5318 | 0.9756 | |
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| 0.4699 | 47.0 | 2444 | 0.5329 | 0.9756 | |
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| 0.4699 | 48.0 | 2496 | 0.5317 | 0.9756 | |
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| 0.4701 | 49.0 | 2548 | 0.5317 | 0.9756 | |
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| 0.4701 | 50.0 | 2600 | 0.5319 | 0.9756 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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