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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: hustvl/yolos-tiny |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: practica_2_kangaroo |
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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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# practica_2_kangaroo |
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This model is a fine-tuned version of [hustvl/yolos-tiny](https://huggingface.co/hustvl/yolos-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6938 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 19 | 0.9975 | |
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| No log | 2.0 | 38 | 0.8337 | |
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| 0.8733 | 3.0 | 57 | 0.9003 | |
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| 0.8733 | 4.0 | 76 | 0.7992 | |
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| 0.8733 | 5.0 | 95 | 0.7225 | |
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| 0.577 | 6.0 | 114 | 0.8095 | |
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| 0.577 | 7.0 | 133 | 0.8329 | |
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| 0.4498 | 8.0 | 152 | 0.7701 | |
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| 0.4498 | 9.0 | 171 | 0.7072 | |
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| 0.4498 | 10.0 | 190 | 0.7774 | |
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| 0.3697 | 11.0 | 209 | 0.7421 | |
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| 0.3697 | 12.0 | 228 | 0.6773 | |
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| 0.3697 | 13.0 | 247 | 0.6309 | |
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| 0.3348 | 14.0 | 266 | 0.7009 | |
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| 0.3348 | 15.0 | 285 | 0.7800 | |
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| 0.2907 | 16.0 | 304 | 0.7364 | |
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| 0.2907 | 17.0 | 323 | 0.6137 | |
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| 0.2907 | 18.0 | 342 | 0.6721 | |
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| 0.2595 | 19.0 | 361 | 0.6353 | |
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| 0.2595 | 20.0 | 380 | 0.6392 | |
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| 0.2595 | 21.0 | 399 | 0.6280 | |
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| 0.244 | 22.0 | 418 | 0.5759 | |
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| 0.244 | 23.0 | 437 | 0.5613 | |
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| 0.2154 | 24.0 | 456 | 0.6886 | |
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| 0.2154 | 25.0 | 475 | 0.6181 | |
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| 0.2154 | 26.0 | 494 | 0.6223 | |
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| 0.1989 | 27.0 | 513 | 0.5730 | |
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| 0.1989 | 28.0 | 532 | 0.6037 | |
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| 0.1848 | 29.0 | 551 | 0.7125 | |
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| 0.1848 | 30.0 | 570 | 0.6218 | |
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| 0.1848 | 31.0 | 589 | 0.5871 | |
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| 0.1686 | 32.0 | 608 | 0.6126 | |
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| 0.1686 | 33.0 | 627 | 0.6017 | |
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| 0.1686 | 34.0 | 646 | 0.7448 | |
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| 0.1667 | 35.0 | 665 | 0.6713 | |
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| 0.1667 | 36.0 | 684 | 0.7800 | |
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| 0.1584 | 37.0 | 703 | 0.7249 | |
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| 0.1584 | 38.0 | 722 | 0.6830 | |
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| 0.1584 | 39.0 | 741 | 0.6575 | |
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| 0.1424 | 40.0 | 760 | 0.6051 | |
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| 0.1424 | 41.0 | 779 | 0.6029 | |
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| 0.1424 | 42.0 | 798 | 0.6182 | |
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| 0.1399 | 43.0 | 817 | 0.5813 | |
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| 0.1399 | 44.0 | 836 | 0.6202 | |
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| 0.1312 | 45.0 | 855 | 0.6301 | |
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| 0.1312 | 46.0 | 874 | 0.7338 | |
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| 0.1312 | 47.0 | 893 | 0.7173 | |
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| 0.1278 | 48.0 | 912 | 0.6548 | |
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| 0.1278 | 49.0 | 931 | 0.7101 | |
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| 0.1166 | 50.0 | 950 | 0.6286 | |
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| 0.1166 | 51.0 | 969 | 0.5544 | |
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| 0.1166 | 52.0 | 988 | 0.6381 | |
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| 0.1108 | 53.0 | 1007 | 0.7138 | |
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| 0.1108 | 54.0 | 1026 | 0.6907 | |
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| 0.1108 | 55.0 | 1045 | 0.7450 | |
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| 0.1097 | 56.0 | 1064 | 0.7085 | |
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| 0.1097 | 57.0 | 1083 | 0.6120 | |
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| 0.1063 | 58.0 | 1102 | 0.6301 | |
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| 0.1063 | 59.0 | 1121 | 0.6081 | |
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| 0.1063 | 60.0 | 1140 | 0.5714 | |
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| 0.1025 | 61.0 | 1159 | 0.6341 | |
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| 0.1025 | 62.0 | 1178 | 0.5742 | |
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| 0.1025 | 63.0 | 1197 | 0.6593 | |
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| 0.1017 | 64.0 | 1216 | 0.6832 | |
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| 0.1017 | 65.0 | 1235 | 0.6422 | |
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| 0.0931 | 66.0 | 1254 | 0.6032 | |
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| 0.0931 | 67.0 | 1273 | 0.6909 | |
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| 0.0931 | 68.0 | 1292 | 0.6501 | |
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| 0.0888 | 69.0 | 1311 | 0.6737 | |
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| 0.0888 | 70.0 | 1330 | 0.7715 | |
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| 0.0888 | 71.0 | 1349 | 0.5660 | |
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| 0.0801 | 72.0 | 1368 | 0.5877 | |
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| 0.0801 | 73.0 | 1387 | 0.6078 | |
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| 0.0848 | 74.0 | 1406 | 0.5911 | |
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| 0.0848 | 75.0 | 1425 | 0.6001 | |
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| 0.0848 | 76.0 | 1444 | 0.7010 | |
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| 0.0827 | 77.0 | 1463 | 0.5590 | |
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| 0.0827 | 78.0 | 1482 | 0.5833 | |
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| 0.0767 | 79.0 | 1501 | 0.5435 | |
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| 0.0767 | 80.0 | 1520 | 0.5577 | |
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| 0.0767 | 81.0 | 1539 | 0.6186 | |
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| 0.0724 | 82.0 | 1558 | 0.6701 | |
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| 0.0724 | 83.0 | 1577 | 0.6461 | |
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| 0.0724 | 84.0 | 1596 | 0.5634 | |
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| 0.0707 | 85.0 | 1615 | 0.7126 | |
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| 0.0707 | 86.0 | 1634 | 0.6726 | |
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| 0.0707 | 87.0 | 1653 | 0.5629 | |
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| 0.0707 | 88.0 | 1672 | 0.6799 | |
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| 0.0707 | 89.0 | 1691 | 0.6672 | |
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| 0.0707 | 90.0 | 1710 | 0.7435 | |
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| 0.0707 | 91.0 | 1729 | 0.6398 | |
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| 0.0707 | 92.0 | 1748 | 0.6162 | |
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| 0.0802 | 93.0 | 1767 | 0.5773 | |
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| 0.0802 | 94.0 | 1786 | 0.6004 | |
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| 0.0659 | 95.0 | 1805 | 0.6375 | |
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| 0.0659 | 96.0 | 1824 | 0.6713 | |
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| 0.0659 | 97.0 | 1843 | 0.7374 | |
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| 0.0651 | 98.0 | 1862 | 0.6655 | |
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| 0.0651 | 99.0 | 1881 | 0.7368 | |
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| 0.0624 | 100.0 | 1900 | 0.6938 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.1 |
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- Tokenizers 0.21.0 |
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