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detr-resnet50-leuk
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: 1.6961
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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.1222 | 1.0 | 121 | 2.3225 |
| 2.7011 | 2.0 | 242 | 2.0470 |
| 2.7217 | 3.0 | 363 | 2.1209 |
| 2.5204 | 4.0 | 484 | 2.0189 |
| 2.4531 | 5.0 | 605 | 1.9293 |
| 2.5448 | 6.0 | 726 | 2.1573 |
| 2.5266 | 7.0 | 847 | 1.9387 |
| 2.385 | 8.0 | 968 | 1.9430 |
| 2.3655 | 9.0 | 1089 | 1.9070 |
| 2.384 | 10.0 | 1210 | 1.8772 |
| 2.4173 | 11.0 | 1331 | 1.9408 |
| 2.4512 | 12.0 | 1452 | 1.9038 |
| 2.4599 | 13.0 | 1573 | 2.0496 |
| 2.382 | 14.0 | 1694 | 1.9044 |
| 2.3739 | 15.0 | 1815 | 1.8649 |
| 2.3066 | 16.0 | 1936 | 1.8339 |
| 2.2597 | 17.0 | 2057 | 1.7873 |
| 2.2254 | 18.0 | 2178 | 1.8041 |
| 2.2674 | 19.0 | 2299 | 1.7946 |
| 2.2109 | 20.0 | 2420 | 1.7831 |
| 2.2812 | 21.0 | 2541 | 1.8024 |
| 2.2648 | 22.0 | 2662 | 1.7854 |
| 2.2161 | 23.0 | 2783 | 1.7622 |
| 2.209 | 24.0 | 2904 | 1.7544 |
| 2.1905 | 25.0 | 3025 | 1.7473 |
| 2.2166 | 26.0 | 3146 | 1.7674 |
| 2.2108 | 27.0 | 3267 | 1.7445 |
| 2.1813 | 28.0 | 3388 | 1.7329 |
| 2.1679 | 29.0 | 3509 | 1.7286 |
| 2.1481 | 30.0 | 3630 | 1.7254 |
| 2.1713 | 31.0 | 3751 | 1.7368 |
| 2.1471 | 32.0 | 3872 | 1.7362 |
| 2.1537 | 33.0 | 3993 | 1.7281 |
| 2.1347 | 34.0 | 4114 | 1.7205 |
| 2.129 | 35.0 | 4235 | 1.7109 |
| 2.1215 | 36.0 | 4356 | 1.7227 |
| 2.1425 | 37.0 | 4477 | 1.7109 |
| 2.1106 | 38.0 | 4598 | 1.6993 |
| 2.0987 | 39.0 | 4719 | 1.6982 |
| 2.1259 | 40.0 | 4840 | 1.6961 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
