detr-r50-finetuned-mist1-gb-4ah-6l
This model is a fine-tuned version of polejowska/detr-r50-cd45rb-8ah-6l on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2166
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: 1e-05
- train_batch_size: 4
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.4044 | 1.0 | 115 | 3.0048 |
| 3.1708 | 2.0 | 230 | 2.9028 |
| 3.0756 | 3.0 | 345 | 2.8538 |
| 2.9769 | 4.0 | 460 | 2.8149 |
| 2.8999 | 5.0 | 575 | 2.7332 |
| 2.8609 | 6.0 | 690 | 2.7212 |
| 2.8338 | 7.0 | 805 | 2.6894 |
| 2.8103 | 8.0 | 920 | 2.7045 |
| 2.8036 | 9.0 | 1035 | 2.7786 |
| 2.7486 | 10.0 | 1150 | 2.6881 |
| 2.7076 | 11.0 | 1265 | 2.6059 |
| 2.7156 | 12.0 | 1380 | 2.6483 |
| 2.6655 | 13.0 | 1495 | 2.5438 |
| 2.6368 | 14.0 | 1610 | 2.5342 |
| 2.5982 | 15.0 | 1725 | 2.5287 |
| 2.6116 | 16.0 | 1840 | 2.4446 |
| 2.5592 | 17.0 | 1955 | 2.4365 |
| 2.5528 | 18.0 | 2070 | 2.4844 |
| 2.5248 | 19.0 | 2185 | 2.4195 |
| 2.4853 | 20.0 | 2300 | 2.4538 |
| 2.5295 | 21.0 | 2415 | 2.5696 |
| 2.5069 | 22.0 | 2530 | 2.4537 |
| 2.4504 | 23.0 | 2645 | 2.5152 |
| 2.4447 | 24.0 | 2760 | 2.4432 |
| 2.4303 | 25.0 | 2875 | 2.4033 |
| 2.4137 | 26.0 | 2990 | 2.3796 |
| 2.41 | 27.0 | 3105 | 2.3599 |
| 2.3816 | 28.0 | 3220 | 2.4018 |
| 2.3752 | 29.0 | 3335 | 2.3116 |
| 2.3929 | 30.0 | 3450 | 2.3105 |
| 2.3791 | 31.0 | 3565 | 2.3677 |
| 2.3639 | 32.0 | 3680 | 2.4312 |
| 2.3475 | 33.0 | 3795 | 2.3052 |
| 2.3429 | 34.0 | 3910 | 2.3222 |
| 2.3115 | 35.0 | 4025 | 2.3126 |
| 2.3276 | 36.0 | 4140 | 2.3154 |
| 2.3126 | 37.0 | 4255 | 2.3534 |
| 2.2934 | 38.0 | 4370 | 2.2566 |
| 2.2901 | 39.0 | 4485 | 2.2748 |
| 2.2622 | 40.0 | 4600 | 2.2620 |
| 2.2707 | 41.0 | 4715 | 2.2336 |
| 2.2338 | 42.0 | 4830 | 2.2242 |
| 2.2457 | 43.0 | 4945 | 2.2192 |
| 2.227 | 44.0 | 5060 | 2.2067 |
| 2.2215 | 45.0 | 5175 | 2.2183 |
| 2.2075 | 46.0 | 5290 | 2.2188 |
| 2.2286 | 47.0 | 5405 | 2.2306 |
| 2.2292 | 48.0 | 5520 | 2.2160 |
| 2.219 | 49.0 | 5635 | 2.2208 |
| 2.2125 | 50.0 | 5750 | 2.2166 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1