conditional-detr-resnet-50_adamw_hf_finetuned_food-roboflow
This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 10.2661
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: 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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4448.7409 | 0.77 | 50 | 2784.9878 |
| 2312.7831 | 1.54 | 100 | 1275.4084 |
| 1139.5262 | 2.31 | 150 | 825.0410 |
| 857.6314 | 3.08 | 200 | 626.2924 |
| 630.5604 | 3.85 | 250 | 492.9028 |
| 518.8461 | 4.62 | 300 | 391.5704 |
| 418.3785 | 5.38 | 350 | 312.8008 |
| 331.9224 | 6.15 | 400 | 250.7763 |
| 261.2112 | 6.92 | 450 | 201.8681 |
| 207.421 | 7.69 | 500 | 163.3361 |
| 172.0157 | 8.46 | 550 | 132.3763 |
| 140.2059 | 9.23 | 600 | 108.1960 |
| 110.3696 | 10.0 | 650 | 89.2497 |
| 95.9428 | 10.77 | 700 | 73.2426 |
| 78.812 | 11.54 | 750 | 61.4362 |
| 64.1493 | 12.31 | 800 | 51.2599 |
| 56.184 | 13.08 | 850 | 43.4741 |
| 46.7644 | 13.85 | 900 | 37.4028 |
| 38.1726 | 14.62 | 950 | 32.6764 |
| 34.7277 | 15.38 | 1000 | 28.1207 |
| 29.9978 | 16.15 | 1050 | 25.0045 |
| 27.5957 | 16.92 | 1100 | 22.3012 |
| 23.6549 | 17.69 | 1150 | 19.9766 |
| 21.4961 | 18.46 | 1200 | 18.2427 |
| 19.3312 | 19.23 | 1250 | 16.8829 |
| 17.8215 | 20.0 | 1300 | 15.5794 |
| 16.2877 | 20.77 | 1350 | 14.5258 |
| 16.0017 | 21.54 | 1400 | 13.5888 |
| 14.6977 | 22.31 | 1450 | 13.0312 |
| 13.9111 | 23.08 | 1500 | 12.4389 |
| 13.5826 | 23.85 | 1550 | 11.8718 |
| 12.5621 | 24.62 | 1600 | 11.6370 |
| 12.1993 | 25.38 | 1650 | 11.1523 |
| 12.2491 | 26.15 | 1700 | 10.8586 |
| 11.5879 | 26.92 | 1750 | 10.6795 |
| 11.4736 | 27.69 | 1800 | 10.5273 |
| 11.5405 | 28.46 | 1850 | 10.4190 |
| 11.5894 | 29.23 | 1900 | 10.3225 |
| 11.0308 | 30.0 | 1950 | 10.2661 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1