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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: timm/mobilenetv3_large_100.miil_in21k |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: test-timm |
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results: [] |
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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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# test-timm |
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This model is a fine-tuned version of [timm/mobilenetv3_large_100.miil_in21k](https://huggingface.co/timm/mobilenetv3_large_100.miil_in21k) on the davanstrien/zenodo-presentations-open-labels dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4897 |
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- Accuracy: 0.7913 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 1337 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 200.0 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 0.6794 | 1.0 | 23 | 0.6063 | 0.6560 | |
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| 0.6215 | 2.0 | 46 | 0.7362 | 0.5833 | |
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| 0.5784 | 3.0 | 69 | 0.7598 | 0.5490 | |
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| 0.5347 | 4.0 | 92 | 0.7638 | 0.5306 | |
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| 0.5307 | 5.0 | 115 | 0.7638 | 0.5235 | |
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| 0.5391 | 6.0 | 138 | 0.7677 | 0.5090 | |
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| 0.48 | 7.0 | 161 | 0.7717 | 0.5108 | |
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| 0.473 | 8.0 | 184 | 0.7756 | 0.5028 | |
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| 0.5014 | 9.0 | 207 | 0.7717 | 0.5054 | |
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| 0.496 | 10.0 | 230 | 0.7717 | 0.5040 | |
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| 0.4688 | 11.0 | 253 | 0.7677 | 0.4972 | |
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| 0.4943 | 12.0 | 276 | 0.7638 | 0.4977 | |
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| 0.5012 | 13.0 | 299 | 0.7717 | 0.5057 | |
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| 0.4639 | 14.0 | 322 | 0.7717 | 0.5010 | |
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| 0.4709 | 15.0 | 345 | 0.7795 | 0.4949 | |
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| 0.4888 | 16.0 | 368 | 0.7835 | 0.4955 | |
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| 0.4594 | 17.0 | 391 | 0.7717 | 0.4986 | |
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| 0.4745 | 18.0 | 414 | 0.7677 | 0.5011 | |
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| 0.4667 | 19.0 | 437 | 0.7756 | 0.4928 | |
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| 0.4551 | 20.0 | 460 | 0.7795 | 0.5055 | |
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| 0.4657 | 21.0 | 483 | 0.7756 | 0.4928 | |
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| 0.4818 | 22.0 | 506 | 0.7756 | 0.5002 | |
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| 0.4633 | 23.0 | 529 | 0.7835 | 0.4946 | |
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| 0.4779 | 24.0 | 552 | 0.7795 | 0.4942 | |
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| 0.4718 | 25.0 | 575 | 0.7835 | 0.4963 | |
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| 0.4511 | 26.0 | 598 | 0.7717 | 0.5011 | |
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| 0.4798 | 27.0 | 621 | 0.7874 | 0.4904 | |
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| 0.4868 | 28.0 | 644 | 0.7835 | 0.4982 | |
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| 0.4653 | 29.0 | 667 | 0.7874 | 0.4988 | |
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| 0.4613 | 30.0 | 690 | 0.7795 | 0.4985 | |
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| 0.4675 | 31.0 | 713 | 0.7717 | 0.5060 | |
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| 0.4587 | 32.0 | 736 | 0.7717 | 0.5059 | |
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| 0.464 | 33.0 | 759 | 0.7795 | 0.5042 | |
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| 0.4374 | 34.0 | 782 | 0.7677 | 0.5063 | |
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| 0.4864 | 35.0 | 805 | 0.7677 | 0.5040 | |
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| 0.4354 | 36.0 | 828 | 0.7717 | 0.5109 | |
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| 0.4655 | 37.0 | 851 | 0.7717 | 0.5107 | |
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| 0.4691 | 38.0 | 874 | 0.7677 | 0.5093 | |
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| 0.4826 | 39.0 | 897 | 0.7717 | 0.5044 | |
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| 0.4577 | 40.0 | 920 | 0.7795 | 0.5000 | |
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| 0.4636 | 41.0 | 943 | 0.7717 | 0.4963 | |
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| 0.4361 | 42.0 | 966 | 0.7717 | 0.4958 | |
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| 0.4534 | 43.0 | 989 | 0.7795 | 0.5008 | |
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| 0.4559 | 44.0 | 1012 | 0.7795 | 0.5025 | |
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| 0.4189 | 45.0 | 1035 | 0.7756 | 0.5014 | |
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| 0.4861 | 46.0 | 1058 | 0.7677 | 0.5004 | |
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| 0.4709 | 47.0 | 1081 | 0.7795 | 0.5005 | |
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| 0.4726 | 48.0 | 1104 | 0.7717 | 0.5008 | |
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| 0.4441 | 49.0 | 1127 | 0.7756 | 0.4988 | |
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| 0.4579 | 50.0 | 1150 | 0.7756 | 0.5000 | |
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| 0.4366 | 51.0 | 1173 | 0.4980 | 0.7756 | |
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| 0.4467 | 52.0 | 1196 | 0.4947 | 0.7795 | |
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| 0.4797 | 53.0 | 1219 | 0.4950 | 0.7756 | |
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| 0.4544 | 54.0 | 1242 | 0.4998 | 0.7717 | |
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| 0.4466 | 55.0 | 1265 | 0.4980 | 0.7795 | |
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| 0.4599 | 56.0 | 1288 | 0.4963 | 0.7835 | |
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| 0.4458 | 57.0 | 1311 | 0.4956 | 0.7874 | |
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| 0.4296 | 58.0 | 1334 | 0.4994 | 0.7874 | |
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| 0.4415 | 59.0 | 1357 | 0.4998 | 0.7835 | |
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| 0.4036 | 60.0 | 1380 | 0.4996 | 0.7795 | |
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| 0.4406 | 61.0 | 1403 | 0.5022 | 0.7913 | |
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| 0.4235 | 62.0 | 1426 | 0.5018 | 0.7913 | |
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| 0.4492 | 63.0 | 1449 | 0.4964 | 0.8031 | |
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| 0.4065 | 64.0 | 1472 | 0.4953 | 0.7874 | |
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| 0.4474 | 65.0 | 1495 | 0.4897 | 0.7913 | |
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| 0.4605 | 66.0 | 1518 | 0.5039 | 0.7795 | |
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| 0.436 | 67.0 | 1541 | 0.5024 | 0.7756 | |
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| 0.4746 | 68.0 | 1564 | 0.5007 | 0.7874 | |
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| 0.4555 | 69.0 | 1587 | 0.5054 | 0.7874 | |
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| 0.433 | 70.0 | 1610 | 0.4974 | 0.7874 | |
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| 0.4503 | 71.0 | 1633 | 0.5096 | 0.7795 | |
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| 0.4424 | 72.0 | 1656 | 0.5040 | 0.7756 | |
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| 0.4331 | 73.0 | 1679 | 0.5056 | 0.7913 | |
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| 0.4263 | 74.0 | 1702 | 0.5026 | 0.7874 | |
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| 0.4305 | 75.0 | 1725 | 0.5033 | 0.7835 | |
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| 0.4271 | 76.0 | 1748 | 0.5015 | 0.7874 | |
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| 0.4635 | 77.0 | 1771 | 0.4988 | 0.7913 | |
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| 0.4212 | 78.0 | 1794 | 0.4994 | 0.7913 | |
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| 0.4154 | 79.0 | 1817 | 0.5044 | 0.7874 | |
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| 0.4288 | 80.0 | 1840 | 0.5033 | 0.7913 | |
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| 0.4211 | 81.0 | 1863 | 0.5050 | 0.7835 | |
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| 0.4022 | 82.0 | 1886 | 0.5021 | 0.7835 | |
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| 0.4477 | 83.0 | 1909 | 0.5096 | 0.7756 | |
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| 0.4091 | 84.0 | 1932 | 0.5017 | 0.7913 | |
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| 0.4284 | 85.0 | 1955 | 0.5094 | 0.7795 | |
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| 0.4317 | 86.0 | 1978 | 0.5056 | 0.7874 | |
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| 0.4011 | 87.0 | 2001 | 0.4992 | 0.7953 | |
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| 0.4043 | 88.0 | 2024 | 0.5106 | 0.7874 | |
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| 0.4233 | 89.0 | 2047 | 0.5083 | 0.7835 | |
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| 0.4383 | 90.0 | 2070 | 0.5016 | 0.7913 | |
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| 0.4328 | 91.0 | 2093 | 0.5062 | 0.7874 | |
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| 0.3978 | 92.0 | 2116 | 0.5026 | 0.7874 | |
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| 0.4052 | 93.0 | 2139 | 0.4964 | 0.7913 | |
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| 0.3938 | 94.0 | 2162 | 0.5036 | 0.7874 | |
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| 0.393 | 95.0 | 2185 | 0.5102 | 0.7835 | |
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| 0.4294 | 96.0 | 2208 | 0.5003 | 0.7874 | |
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| 0.4122 | 97.0 | 2231 | 0.5013 | 0.7913 | |
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| 0.4207 | 98.0 | 2254 | 0.5076 | 0.7874 | |
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| 0.4127 | 99.0 | 2277 | 0.5040 | 0.7835 | |
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| 0.441 | 100.0 | 2300 | 0.5022 | 0.7835 | |
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| 0.3938 | 101.0 | 2323 | 0.4975 | 0.7992 | |
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| 0.4109 | 102.0 | 2346 | 0.5019 | 0.7913 | |
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| 0.4299 | 103.0 | 2369 | 0.5060 | 0.7874 | |
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| 0.4148 | 104.0 | 2392 | 0.5038 | 0.7874 | |
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| 0.4179 | 105.0 | 2415 | 0.5064 | 0.7835 | |
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| 0.4352 | 106.0 | 2438 | 0.5059 | 0.7874 | |
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| 0.4027 | 107.0 | 2461 | 0.5025 | 0.7953 | |
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| 0.4002 | 108.0 | 2484 | 0.5020 | 0.7874 | |
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| 0.3988 | 109.0 | 2507 | 0.5063 | 0.7874 | |
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| 0.4095 | 110.0 | 2530 | 0.5034 | 0.7913 | |
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| 0.4001 | 111.0 | 2553 | 0.5054 | 0.7874 | |
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| 0.4201 | 112.0 | 2576 | 0.5076 | 0.7992 | |
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| 0.4134 | 113.0 | 2599 | 0.5070 | 0.7953 | |
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| 0.3614 | 114.0 | 2622 | 0.5033 | 0.7835 | |
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| 0.3928 | 115.0 | 2645 | 0.5043 | 0.7874 | |
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| 0.435 | 116.0 | 2668 | 0.4999 | 0.7874 | |
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| 0.4162 | 117.0 | 2691 | 0.5132 | 0.7874 | |
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| 0.4078 | 118.0 | 2714 | 0.5088 | 0.7795 | |
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| 0.4025 | 119.0 | 2737 | 0.5075 | 0.7835 | |
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| 0.4096 | 120.0 | 2760 | 0.5023 | 0.7835 | |
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| 0.3879 | 121.0 | 2783 | 0.5063 | 0.7835 | |
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| 0.4033 | 122.0 | 2806 | 0.5001 | 0.7874 | |
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| 0.3927 | 123.0 | 2829 | 0.5087 | 0.7795 | |
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| 0.3803 | 124.0 | 2852 | 0.5150 | 0.7913 | |
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| 0.4248 | 125.0 | 2875 | 0.5150 | 0.7835 | |
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| 0.3874 | 126.0 | 2898 | 0.5158 | 0.7874 | |
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| 0.3646 | 127.0 | 2921 | 0.4980 | 0.8031 | |
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| 0.4115 | 128.0 | 2944 | 0.5077 | 0.7913 | |
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| 0.385 | 129.0 | 2967 | 0.5153 | 0.7913 | |
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| 0.4064 | 130.0 | 2990 | 0.5114 | 0.7953 | |
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| 0.4168 | 131.0 | 3013 | 0.5057 | 0.7992 | |
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| 0.4319 | 132.0 | 3036 | 0.5041 | 0.7953 | |
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| 0.4234 | 133.0 | 3059 | 0.5119 | 0.7992 | |
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| 0.3721 | 134.0 | 3082 | 0.5118 | 0.7874 | |
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| 0.3709 | 135.0 | 3105 | 0.5078 | 0.7913 | |
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| 0.4149 | 136.0 | 3128 | 0.5164 | 0.7795 | |
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| 0.416 | 137.0 | 3151 | 0.5123 | 0.7835 | |
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| 0.406 | 138.0 | 3174 | 0.5116 | 0.7913 | |
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| 0.3613 | 139.0 | 3197 | 0.5170 | 0.7913 | |
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| 0.3786 | 140.0 | 3220 | 0.5099 | 0.8031 | |
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| 0.3976 | 141.0 | 3243 | 0.5111 | 0.7913 | |
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| 0.371 | 142.0 | 3266 | 0.5081 | 0.7953 | |
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| 0.4056 | 143.0 | 3289 | 0.5098 | 0.7913 | |
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| 0.4214 | 144.0 | 3312 | 0.5085 | 0.7953 | |
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| 0.3832 | 145.0 | 3335 | 0.5084 | 0.7953 | |
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| 0.3762 | 146.0 | 3358 | 0.5061 | 0.7913 | |
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| 0.4118 | 147.0 | 3381 | 0.5111 | 0.7992 | |
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| 0.3866 | 148.0 | 3404 | 0.5092 | 0.8071 | |
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| 0.3869 | 149.0 | 3427 | 0.5122 | 0.7953 | |
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| 0.3734 | 150.0 | 3450 | 0.5117 | 0.7953 | |
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| 0.4061 | 151.0 | 3473 | 0.5095 | 0.7913 | |
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| 0.3705 | 152.0 | 3496 | 0.5171 | 0.7953 | |
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| 0.3873 | 153.0 | 3519 | 0.5179 | 0.7953 | |
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| 0.3927 | 154.0 | 3542 | 0.5117 | 0.7992 | |
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| 0.3807 | 155.0 | 3565 | 0.5133 | 0.7953 | |
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| 0.3761 | 156.0 | 3588 | 0.5140 | 0.7913 | |
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| 0.3964 | 157.0 | 3611 | 0.5118 | 0.7953 | |
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| 0.39 | 158.0 | 3634 | 0.5122 | 0.8031 | |
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| 0.3943 | 159.0 | 3657 | 0.5126 | 0.8031 | |
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| 0.3417 | 160.0 | 3680 | 0.5097 | 0.7992 | |
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| 0.3996 | 161.0 | 3703 | 0.5048 | 0.7913 | |
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| 0.4 | 162.0 | 3726 | 0.5148 | 0.7953 | |
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| 0.4051 | 163.0 | 3749 | 0.5150 | 0.7874 | |
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| 0.3973 | 164.0 | 3772 | 0.5037 | 0.8031 | |
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| 0.3963 | 165.0 | 3795 | 0.5048 | 0.7953 | |
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| 0.3568 | 166.0 | 3818 | 0.5168 | 0.7913 | |
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| 0.3995 | 167.0 | 3841 | 0.5096 | 0.7913 | |
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| 0.3628 | 168.0 | 3864 | 0.5102 | 0.7953 | |
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| 0.3836 | 169.0 | 3887 | 0.5133 | 0.7953 | |
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| 0.3646 | 170.0 | 3910 | 0.5099 | 0.8031 | |
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| 0.3789 | 171.0 | 3933 | 0.5151 | 0.7874 | |
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| 0.3832 | 172.0 | 3956 | 0.5149 | 0.8031 | |
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| 0.3476 | 173.0 | 3979 | 0.5178 | 0.7835 | |
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| 0.3806 | 174.0 | 4002 | 0.5081 | 0.7992 | |
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| 0.4053 | 175.0 | 4025 | 0.5100 | 0.7874 | |
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| 0.3986 | 176.0 | 4048 | 0.5189 | 0.7992 | |
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| 0.3827 | 177.0 | 4071 | 0.5129 | 0.7992 | |
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| 0.3892 | 178.0 | 4094 | 0.5099 | 0.7874 | |
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| 0.3955 | 179.0 | 4117 | 0.5212 | 0.7992 | |
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| 0.4077 | 180.0 | 4140 | 0.5102 | 0.7953 | |
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| 0.3579 | 181.0 | 4163 | 0.5100 | 0.7953 | |
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| 0.3666 | 182.0 | 4186 | 0.5248 | 0.7835 | |
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| 0.3746 | 183.0 | 4209 | 0.5220 | 0.7874 | |
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| 0.3867 | 184.0 | 4232 | 0.5173 | 0.7913 | |
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| 0.4024 | 185.0 | 4255 | 0.5248 | 0.7874 | |
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| 0.4014 | 186.0 | 4278 | 0.5085 | 0.7913 | |
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| 0.3445 | 187.0 | 4301 | 0.5137 | 0.8031 | |
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| 0.382 | 188.0 | 4324 | 0.5213 | 0.7913 | |
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| 0.3673 | 189.0 | 4347 | 0.5242 | 0.7913 | |
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| 0.3631 | 190.0 | 4370 | 0.5146 | 0.7913 | |
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| 0.393 | 191.0 | 4393 | 0.5098 | 0.7835 | |
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| 0.3806 | 192.0 | 4416 | 0.5134 | 0.7992 | |
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| 0.3789 | 193.0 | 4439 | 0.5127 | 0.7992 | |
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| 0.3717 | 194.0 | 4462 | 0.5184 | 0.7913 | |
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| 0.361 | 195.0 | 4485 | 0.5186 | 0.7835 | |
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| 0.3722 | 196.0 | 4508 | 0.5107 | 0.7953 | |
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| 0.3551 | 197.0 | 4531 | 0.5175 | 0.7953 | |
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| 0.3649 | 198.0 | 4554 | 0.5136 | 0.7992 | |
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| 0.3749 | 199.0 | 4577 | 0.5193 | 0.7913 | |
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| 0.3782 | 200.0 | 4600 | 0.5182 | 0.7992 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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