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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-print |
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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: 0.9263157894736842 |
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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-print |
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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: 0.1811 |
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- Accuracy: 0.9263 |
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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: 100 |
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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 | 0.8889 | 6 | 1.6653 | 0.1158 | |
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| 1.6915 | 1.9259 | 13 | 1.5942 | 0.2316 | |
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| 1.5895 | 2.9630 | 20 | 1.4918 | 0.3895 | |
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| 1.5895 | 4.0 | 27 | 1.3637 | 0.5053 | |
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| 1.433 | 4.8889 | 33 | 1.2241 | 0.6737 | |
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| 1.2158 | 5.9259 | 40 | 1.0279 | 0.7474 | |
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| 1.2158 | 6.9630 | 47 | 0.8303 | 0.8105 | |
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| 0.9438 | 8.0 | 54 | 0.6756 | 0.8211 | |
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| 0.727 | 8.8889 | 60 | 0.5751 | 0.8421 | |
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| 0.727 | 9.9259 | 67 | 0.4679 | 0.8632 | |
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| 0.5516 | 10.9630 | 74 | 0.4432 | 0.8526 | |
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| 0.4337 | 12.0 | 81 | 0.3815 | 0.8526 | |
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| 0.4337 | 12.8889 | 87 | 0.3641 | 0.8842 | |
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| 0.3757 | 13.9259 | 94 | 0.3233 | 0.8737 | |
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| 0.3017 | 14.9630 | 101 | 0.3230 | 0.9158 | |
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| 0.3017 | 16.0 | 108 | 0.3018 | 0.8842 | |
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| 0.2495 | 16.8889 | 114 | 0.3445 | 0.9053 | |
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| 0.2177 | 17.9259 | 121 | 0.2987 | 0.8947 | |
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| 0.2177 | 18.9630 | 128 | 0.2727 | 0.8947 | |
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| 0.1738 | 20.0 | 135 | 0.2865 | 0.8842 | |
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| 0.1572 | 20.8889 | 141 | 0.2646 | 0.9263 | |
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| 0.1572 | 21.9259 | 148 | 0.3100 | 0.9053 | |
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| 0.1165 | 22.9630 | 155 | 0.3039 | 0.9263 | |
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| 0.1057 | 24.0 | 162 | 0.3023 | 0.9053 | |
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| 0.1057 | 24.8889 | 168 | 0.2254 | 0.9158 | |
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| 0.0825 | 25.9259 | 175 | 0.3308 | 0.8737 | |
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| 0.0795 | 26.9630 | 182 | 0.2040 | 0.9368 | |
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| 0.0795 | 28.0 | 189 | 0.2148 | 0.9263 | |
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| 0.072 | 28.8889 | 195 | 0.3450 | 0.8632 | |
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| 0.0701 | 29.9259 | 202 | 0.2418 | 0.9263 | |
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| 0.0701 | 30.9630 | 209 | 0.2495 | 0.9263 | |
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| 0.0635 | 32.0 | 216 | 0.3267 | 0.8947 | |
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| 0.0537 | 32.8889 | 222 | 0.3728 | 0.9158 | |
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| 0.0537 | 33.9259 | 229 | 0.2852 | 0.9053 | |
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| 0.0607 | 34.9630 | 236 | 0.2386 | 0.9474 | |
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| 0.052 | 36.0 | 243 | 0.2070 | 0.9158 | |
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| 0.052 | 36.8889 | 249 | 0.1860 | 0.9474 | |
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| 0.049 | 37.9259 | 256 | 0.3069 | 0.8947 | |
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| 0.0578 | 38.9630 | 263 | 0.4477 | 0.8737 | |
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| 0.0533 | 40.0 | 270 | 0.2612 | 0.8947 | |
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| 0.0533 | 40.8889 | 276 | 0.2649 | 0.8842 | |
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| 0.0505 | 41.9259 | 283 | 0.1950 | 0.9263 | |
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| 0.0433 | 42.9630 | 290 | 0.2903 | 0.8842 | |
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| 0.0433 | 44.0 | 297 | 0.2526 | 0.9368 | |
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| 0.0395 | 44.8889 | 303 | 0.3016 | 0.8842 | |
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| 0.035 | 45.9259 | 310 | 0.3509 | 0.8947 | |
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| 0.035 | 46.9630 | 317 | 0.2943 | 0.8842 | |
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| 0.0335 | 48.0 | 324 | 0.2613 | 0.8842 | |
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| 0.0408 | 48.8889 | 330 | 0.2165 | 0.9158 | |
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| 0.0408 | 49.9259 | 337 | 0.2872 | 0.9263 | |
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| 0.0244 | 50.9630 | 344 | 0.3134 | 0.8842 | |
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| 0.0323 | 52.0 | 351 | 0.3006 | 0.9158 | |
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| 0.0323 | 52.8889 | 357 | 0.3758 | 0.8737 | |
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| 0.0241 | 53.9259 | 364 | 0.3033 | 0.9263 | |
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| 0.0193 | 54.9630 | 371 | 0.2741 | 0.9368 | |
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| 0.0193 | 56.0 | 378 | 0.1684 | 0.9368 | |
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| 0.0273 | 56.8889 | 384 | 0.2403 | 0.9474 | |
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| 0.0244 | 57.9259 | 391 | 0.1500 | 0.9474 | |
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| 0.0244 | 58.9630 | 398 | 0.1377 | 0.9368 | |
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| 0.0268 | 60.0 | 405 | 0.1898 | 0.9158 | |
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| 0.0405 | 60.8889 | 411 | 0.1756 | 0.9053 | |
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| 0.0405 | 61.9259 | 418 | 0.1907 | 0.9263 | |
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| 0.0219 | 62.9630 | 425 | 0.1790 | 0.9053 | |
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| 0.0329 | 64.0 | 432 | 0.1885 | 0.9368 | |
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| 0.0329 | 64.8889 | 438 | 0.1550 | 0.9368 | |
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| 0.019 | 65.9259 | 445 | 0.1811 | 0.9158 | |
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| 0.0205 | 66.9630 | 452 | 0.2166 | 0.9263 | |
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| 0.0205 | 68.0 | 459 | 0.1701 | 0.9053 | |
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| 0.0232 | 68.8889 | 465 | 0.2153 | 0.9158 | |
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| 0.0269 | 69.9259 | 472 | 0.2229 | 0.9263 | |
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| 0.0269 | 70.9630 | 479 | 0.2237 | 0.9263 | |
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| 0.0306 | 72.0 | 486 | 0.1828 | 0.9368 | |
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| 0.0298 | 72.8889 | 492 | 0.1448 | 0.9368 | |
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| 0.0298 | 73.9259 | 499 | 0.1948 | 0.9158 | |
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| 0.0154 | 74.9630 | 506 | 0.2570 | 0.9158 | |
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| 0.0193 | 76.0 | 513 | 0.2462 | 0.9263 | |
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| 0.0193 | 76.8889 | 519 | 0.2194 | 0.9158 | |
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| 0.0188 | 77.9259 | 526 | 0.2254 | 0.9158 | |
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| 0.0198 | 78.9630 | 533 | 0.1924 | 0.9263 | |
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| 0.0147 | 80.0 | 540 | 0.1525 | 0.9368 | |
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| 0.0147 | 80.8889 | 546 | 0.1314 | 0.9474 | |
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| 0.0282 | 81.9259 | 553 | 0.1381 | 0.9368 | |
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| 0.0168 | 82.9630 | 560 | 0.1496 | 0.9158 | |
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| 0.0168 | 84.0 | 567 | 0.1806 | 0.9263 | |
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| 0.018 | 84.8889 | 573 | 0.2080 | 0.9263 | |
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| 0.0172 | 85.9259 | 580 | 0.2199 | 0.9158 | |
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| 0.0172 | 86.9630 | 587 | 0.1939 | 0.9263 | |
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| 0.0117 | 88.0 | 594 | 0.1815 | 0.9263 | |
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| 0.0149 | 88.8889 | 600 | 0.1811 | 0.9263 | |
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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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