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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-tiny-1k-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: convnextv2-tiny-1k-224-finetuned-sleeve-length |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8620689655172413 |
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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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# convnextv2-tiny-1k-224-finetuned-sleeve-length |
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This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5496 |
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- Accuracy: 0.8621 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 80 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.96 | 6 | 1.7957 | 0.2299 | |
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| 1.8656 | 1.92 | 12 | 1.7704 | 0.2759 | |
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| 1.8656 | 2.88 | 18 | 1.7382 | 0.3218 | |
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| 1.7835 | 4.0 | 25 | 1.6674 | 0.3793 | |
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| 1.664 | 4.96 | 31 | 1.5982 | 0.4253 | |
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| 1.664 | 5.92 | 37 | 1.4861 | 0.4368 | |
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| 1.5072 | 6.88 | 43 | 1.3645 | 0.4713 | |
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| 1.3304 | 8.0 | 50 | 1.2859 | 0.4598 | |
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| 1.3304 | 8.96 | 56 | 1.2796 | 0.4713 | |
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| 1.1651 | 9.92 | 62 | 1.2456 | 0.5172 | |
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| 1.1651 | 10.88 | 68 | 1.1667 | 0.5402 | |
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| 1.0876 | 12.0 | 75 | 1.1510 | 0.5632 | |
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| 1.0046 | 12.96 | 81 | 1.0510 | 0.6092 | |
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| 1.0046 | 13.92 | 87 | 1.0338 | 0.5862 | |
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| 0.9465 | 14.88 | 93 | 0.9883 | 0.5862 | |
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| 0.8699 | 16.0 | 100 | 0.9882 | 0.5632 | |
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| 0.8699 | 16.96 | 106 | 0.9276 | 0.5747 | |
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| 0.7969 | 17.92 | 112 | 0.9145 | 0.5862 | |
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| 0.7969 | 18.88 | 118 | 0.8144 | 0.6667 | |
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| 0.7254 | 20.0 | 125 | 0.7587 | 0.6667 | |
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| 0.6447 | 20.96 | 131 | 0.6990 | 0.7471 | |
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| 0.6447 | 21.92 | 137 | 0.7042 | 0.7241 | |
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| 0.6021 | 22.88 | 143 | 0.6526 | 0.7701 | |
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| 0.516 | 24.0 | 150 | 0.6485 | 0.8046 | |
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| 0.516 | 24.96 | 156 | 0.5803 | 0.8161 | |
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| 0.4497 | 25.92 | 162 | 0.6085 | 0.8046 | |
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| 0.4497 | 26.88 | 168 | 0.6095 | 0.8046 | |
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| 0.3935 | 28.0 | 175 | 0.5372 | 0.8276 | |
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| 0.3321 | 28.96 | 181 | 0.5829 | 0.8161 | |
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| 0.3321 | 29.92 | 187 | 0.6205 | 0.8161 | |
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| 0.3007 | 30.88 | 193 | 0.5150 | 0.8276 | |
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| 0.2618 | 32.0 | 200 | 0.6069 | 0.8391 | |
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| 0.2618 | 32.96 | 206 | 0.5273 | 0.8391 | |
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| 0.2411 | 33.92 | 212 | 0.4727 | 0.8621 | |
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| 0.2411 | 34.88 | 218 | 0.4611 | 0.8736 | |
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| 0.2108 | 36.0 | 225 | 0.5696 | 0.8506 | |
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| 0.2143 | 36.96 | 231 | 0.4944 | 0.8621 | |
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| 0.2143 | 37.92 | 237 | 0.5628 | 0.8161 | |
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| 0.1663 | 38.88 | 243 | 0.6131 | 0.8046 | |
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| 0.1714 | 40.0 | 250 | 0.4962 | 0.8506 | |
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| 0.1714 | 40.96 | 256 | 0.5023 | 0.8391 | |
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| 0.174 | 41.92 | 262 | 0.4842 | 0.8276 | |
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| 0.174 | 42.88 | 268 | 0.4679 | 0.8276 | |
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| 0.138 | 44.0 | 275 | 0.6271 | 0.8161 | |
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| 0.1437 | 44.96 | 281 | 0.5326 | 0.8506 | |
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| 0.1437 | 45.92 | 287 | 0.5655 | 0.8161 | |
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| 0.136 | 46.88 | 293 | 0.4672 | 0.8391 | |
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| 0.1401 | 48.0 | 300 | 0.4990 | 0.8621 | |
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| 0.1401 | 48.96 | 306 | 0.5445 | 0.8276 | |
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| 0.1281 | 49.92 | 312 | 0.4761 | 0.8736 | |
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| 0.1281 | 50.88 | 318 | 0.5665 | 0.8506 | |
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| 0.1156 | 52.0 | 325 | 0.5090 | 0.8506 | |
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| 0.0981 | 52.96 | 331 | 0.5152 | 0.8506 | |
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| 0.0981 | 53.92 | 337 | 0.5466 | 0.8161 | |
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| 0.1055 | 54.88 | 343 | 0.5390 | 0.8276 | |
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| 0.112 | 56.0 | 350 | 0.5574 | 0.8506 | |
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| 0.112 | 56.96 | 356 | 0.5449 | 0.8506 | |
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| 0.0855 | 57.92 | 362 | 0.5390 | 0.8506 | |
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| 0.0855 | 58.88 | 368 | 0.5206 | 0.8506 | |
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| 0.0899 | 60.0 | 375 | 0.5476 | 0.8621 | |
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| 0.1026 | 60.96 | 381 | 0.5344 | 0.8506 | |
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| 0.1026 | 61.92 | 387 | 0.5531 | 0.8391 | |
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| 0.0799 | 62.88 | 393 | 0.5723 | 0.8276 | |
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| 0.0844 | 64.0 | 400 | 0.5340 | 0.8161 | |
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| 0.0844 | 64.96 | 406 | 0.5236 | 0.8736 | |
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| 0.0724 | 65.92 | 412 | 0.6137 | 0.8391 | |
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| 0.0724 | 66.88 | 418 | 0.5825 | 0.8276 | |
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| 0.0867 | 68.0 | 425 | 0.5105 | 0.8621 | |
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| 0.071 | 68.96 | 431 | 0.5272 | 0.8506 | |
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| 0.071 | 69.92 | 437 | 0.5524 | 0.8506 | |
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| 0.0723 | 70.88 | 443 | 0.5508 | 0.8391 | |
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| 0.0748 | 72.0 | 450 | 0.5689 | 0.8161 | |
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| 0.0748 | 72.96 | 456 | 0.5556 | 0.8506 | |
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| 0.0589 | 73.92 | 462 | 0.5452 | 0.8506 | |
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| 0.0589 | 74.88 | 468 | 0.5475 | 0.8621 | |
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| 0.0719 | 76.0 | 475 | 0.5484 | 0.8621 | |
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| 0.0801 | 76.8 | 480 | 0.5496 | 0.8621 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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