detr-resnet-50-CD45RB-100
This model is a fine-tuned version of facebook/detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6658
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.1316 | 1.0 | 94 | 2.3431 |
2.812 | 2.0 | 188 | 2.2115 |
2.8118 | 3.0 | 282 | 1.9844 |
2.5555 | 4.0 | 376 | 1.9309 |
2.4803 | 5.0 | 470 | 1.8790 |
2.5099 | 6.0 | 564 | 2.0294 |
2.5365 | 7.0 | 658 | 1.8845 |
2.4593 | 8.0 | 752 | 1.8699 |
2.4248 | 9.0 | 846 | 1.7946 |
2.4017 | 10.0 | 940 | 1.7905 |
2.4523 | 11.0 | 1034 | 1.8319 |
2.4407 | 12.0 | 1128 | 1.8370 |
2.3727 | 13.0 | 1222 | 1.8001 |
2.317 | 14.0 | 1316 | 1.7492 |
2.3292 | 15.0 | 1410 | 1.7531 |
2.3086 | 16.0 | 1504 | 1.7637 |
2.3175 | 17.0 | 1598 | 1.7302 |
2.3002 | 18.0 | 1692 | 1.7216 |
2.2756 | 19.0 | 1786 | 1.7345 |
2.2656 | 20.0 | 1880 | 1.7225 |
2.3083 | 21.0 | 1974 | 1.7549 |
2.2542 | 22.0 | 2068 | 1.7175 |
2.2262 | 23.0 | 2162 | 1.6998 |
2.2644 | 24.0 | 2256 | 1.7020 |
2.2392 | 25.0 | 2350 | 1.6933 |
2.228 | 26.0 | 2444 | 1.7434 |
2.2284 | 27.0 | 2538 | 1.7070 |
2.2019 | 28.0 | 2632 | 1.6977 |
2.1804 | 29.0 | 2726 | 1.6867 |
2.1939 | 30.0 | 2820 | 1.6859 |
2.1863 | 31.0 | 2914 | 1.6802 |
2.2009 | 32.0 | 3008 | 1.6940 |
2.1894 | 33.0 | 3102 | 1.6720 |
2.1759 | 34.0 | 3196 | 1.6700 |
2.1575 | 35.0 | 3290 | 1.6713 |
2.1715 | 36.0 | 3384 | 1.7287 |
2.2125 | 37.0 | 3478 | 1.6994 |
2.2032 | 38.0 | 3572 | 1.6896 |
2.21 | 39.0 | 3666 | 1.6793 |
2.1837 | 40.0 | 3760 | 1.6747 |
2.2136 | 41.0 | 3854 | 1.6728 |
2.1825 | 42.0 | 3948 | 1.6641 |
2.1419 | 43.0 | 4042 | 1.6829 |
2.1695 | 44.0 | 4136 | 1.6625 |
2.1478 | 45.0 | 4230 | 1.6680 |
2.1464 | 46.0 | 4324 | 1.6795 |
2.1809 | 47.0 | 4418 | 1.6775 |
2.174 | 48.0 | 4512 | 1.6668 |
2.1391 | 49.0 | 4606 | 1.6559 |
2.1466 | 50.0 | 4700 | 1.6658 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
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