chickens-repro-4
This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.
It achieves the following results on the evaluation set:
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 60
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
| 1.2251 |
1.0 |
227 |
1.1143 |
| 1.1432 |
2.0 |
454 |
1.3992 |
| 1.0496 |
3.0 |
681 |
0.9853 |
| 0.9896 |
4.0 |
908 |
0.7757 |
| 0.8727 |
5.0 |
1135 |
0.7749 |
| 0.7478 |
6.0 |
1362 |
0.7531 |
| 0.694 |
7.0 |
1589 |
0.5933 |
| 0.7923 |
8.0 |
1816 |
0.6223 |
| 0.8413 |
9.0 |
2043 |
0.6116 |
| 0.8007 |
10.0 |
2270 |
0.8077 |
| 0.7769 |
11.0 |
2497 |
0.7307 |
| 0.7564 |
12.0 |
2724 |
0.6538 |
| 0.7178 |
13.0 |
2951 |
0.5011 |
| 0.724 |
14.0 |
3178 |
0.7358 |
| 0.7586 |
15.0 |
3405 |
0.6229 |
| 0.7284 |
16.0 |
3632 |
0.6627 |
| 0.6092 |
17.0 |
3859 |
0.5987 |
| 0.6531 |
18.0 |
4086 |
0.6447 |
| 0.5879 |
19.0 |
4313 |
0.4965 |
| 0.62 |
20.0 |
4540 |
0.4803 |
| 0.5851 |
21.0 |
4767 |
0.5303 |
| 0.5981 |
22.0 |
4994 |
0.4260 |
| 0.5593 |
23.0 |
5221 |
0.4870 |
| 0.6139 |
24.0 |
5448 |
0.4931 |
| 0.5381 |
25.0 |
5675 |
0.4639 |
| 0.5569 |
26.0 |
5902 |
0.4438 |
| 0.5432 |
27.0 |
6129 |
0.4747 |
| 0.5557 |
28.0 |
6356 |
0.4214 |
| 0.4997 |
29.0 |
6583 |
0.4308 |
| 0.5008 |
30.0 |
6810 |
0.3995 |
| 0.4966 |
31.0 |
7037 |
0.3612 |
| 0.4636 |
32.0 |
7264 |
0.4262 |
| 0.4566 |
33.0 |
7491 |
0.3896 |
| 0.4301 |
34.0 |
7718 |
0.3916 |
| 0.4501 |
35.0 |
7945 |
0.3290 |
| 0.4454 |
36.0 |
8172 |
0.3854 |
| 0.4313 |
37.0 |
8399 |
0.3072 |
| 0.4004 |
38.0 |
8626 |
0.3387 |
| 0.3943 |
39.0 |
8853 |
0.3349 |
| 0.397 |
40.0 |
9080 |
0.2835 |
| 0.3962 |
41.0 |
9307 |
0.2743 |
| 0.3924 |
42.0 |
9534 |
0.3099 |
| 0.373 |
43.0 |
9761 |
0.2811 |
| 0.3567 |
44.0 |
9988 |
0.2673 |
| 0.3675 |
45.0 |
10215 |
0.2863 |
| 0.3687 |
46.0 |
10442 |
0.2822 |
| 0.3495 |
47.0 |
10669 |
0.2650 |
| 0.3413 |
48.0 |
10896 |
0.2669 |
| 0.3495 |
49.0 |
11123 |
0.2664 |
| 0.3208 |
50.0 |
11350 |
0.2788 |
| 0.3348 |
51.0 |
11577 |
0.2763 |
| 0.34 |
52.0 |
11804 |
0.2615 |
| 0.3595 |
53.0 |
12031 |
0.2553 |
| 0.3319 |
54.0 |
12258 |
0.2588 |
| 0.342 |
55.0 |
12485 |
0.2597 |
| 0.3329 |
56.0 |
12712 |
0.2542 |
| 0.3357 |
57.0 |
12939 |
0.2543 |
| 0.3364 |
58.0 |
13166 |
0.2504 |
| 0.3278 |
59.0 |
13393 |
0.2535 |
| 0.3351 |
60.0 |
13620 |
0.2536 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
