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---
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
model-index:
- name: drone-DinoVdeau-from-binary-large-2024_11_14-batch-size16_freeze_probs
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# drone-DinoVdeau-from-binary-large-2024_11_14-batch-size16_freeze_probs
This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4061
- Rmse: 0.2019
- Mae: 0.1446
- Kl Divergence: 0.9802
- Explained Variance: 0.3860
- Learning Rate: 0.0000
## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Kl Divergence | Explained Variance | Rate |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:-------------:|:------------------:|:------:|
| No log | 1.0 | 438 | 0.4306 | 0.2210 | 0.1621 | 1.0069 | 0.2882 | 0.001 |
| 0.4808 | 2.0 | 876 | 0.4246 | 0.2179 | 0.1547 | 1.3119 | 0.3118 | 0.001 |
| 0.421 | 3.0 | 1314 | 0.4223 | 0.2158 | 0.1554 | 1.0982 | 0.3192 | 0.001 |
| 0.4151 | 4.0 | 1752 | 0.4191 | 0.2142 | 0.1552 | 1.0414 | 0.3351 | 0.001 |
| 0.4114 | 5.0 | 2190 | 0.4171 | 0.2123 | 0.1541 | 1.0698 | 0.3384 | 0.001 |
| 0.4089 | 6.0 | 2628 | 0.4209 | 0.2140 | 0.1520 | 1.1959 | 0.3311 | 0.001 |
| 0.4091 | 7.0 | 3066 | 0.4166 | 0.2126 | 0.1530 | 1.1709 | 0.3382 | 0.001 |
| 0.4071 | 8.0 | 3504 | 0.4195 | 0.2143 | 0.1556 | 0.9712 | 0.3346 | 0.001 |
| 0.4071 | 9.0 | 3942 | 0.4167 | 0.2121 | 0.1524 | 1.1432 | 0.3415 | 0.001 |
| 0.4062 | 10.0 | 4380 | 0.4186 | 0.2139 | 0.1535 | 0.9121 | 0.3420 | 0.001 |
| 0.4052 | 11.0 | 4818 | 0.4156 | 0.2114 | 0.1536 | 0.9950 | 0.3442 | 0.001 |
| 0.406 | 12.0 | 5256 | 0.4188 | 0.2139 | 0.1555 | 1.0106 | 0.3390 | 0.001 |
| 0.4058 | 13.0 | 5694 | 0.4163 | 0.2121 | 0.1553 | 1.1482 | 0.3425 | 0.001 |
| 0.4056 | 14.0 | 6132 | 0.4193 | 0.2138 | 0.1546 | 1.2111 | 0.3286 | 0.001 |
| 0.4033 | 15.0 | 6570 | 0.4162 | 0.2121 | 0.1542 | 1.2043 | 0.3402 | 0.001 |
| 0.4057 | 16.0 | 7008 | 0.4139 | 0.2102 | 0.1528 | 1.0828 | 0.3500 | 0.001 |
| 0.4057 | 17.0 | 7446 | 0.4171 | 0.2118 | 0.1564 | 1.0006 | 0.3430 | 0.001 |
| 0.405 | 18.0 | 7884 | 0.4146 | 0.2107 | 0.1507 | 1.0514 | 0.3499 | 0.001 |
| 0.4035 | 19.0 | 8322 | 0.4186 | 0.2114 | 0.1532 | 0.9575 | 0.3468 | 0.001 |
| 0.4031 | 20.0 | 8760 | 0.4143 | 0.2108 | 0.1513 | 1.1648 | 0.3487 | 0.001 |
| 0.4048 | 21.0 | 9198 | 0.4195 | 0.2123 | 0.1533 | 1.2950 | 0.3385 | 0.001 |
| 0.4055 | 22.0 | 9636 | 0.4340 | 0.2110 | 0.1524 | inf | 0.3463 | 0.001 |
| 0.4022 | 23.0 | 10074 | 0.4327 | 0.2085 | 0.1517 | nan | 0.3621 | 0.0001 |
| 0.3978 | 24.0 | 10512 | 0.4385 | 0.2092 | 0.1493 | nan | 0.3583 | 0.0001 |
| 0.3978 | 25.0 | 10950 | 0.4272 | 0.2074 | 0.1490 | inf | 0.3649 | 0.0001 |
| 0.3988 | 26.0 | 11388 | 0.4105 | 0.2075 | 0.1480 | 1.1903 | 0.3644 | 0.0001 |
| 0.3958 | 27.0 | 11826 | 0.4096 | 0.2067 | 0.1494 | 0.9915 | 0.3688 | 0.0001 |
| 0.3965 | 28.0 | 12264 | 0.4104 | 0.2075 | 0.1493 | 0.9669 | 0.3681 | 0.0001 |
| 0.396 | 29.0 | 12702 | 0.4097 | 0.2069 | 0.1469 | 1.0433 | 0.3696 | 0.0001 |
| 0.3936 | 30.0 | 13140 | 0.4094 | 0.2065 | 0.1490 | 0.9082 | 0.3731 | 0.0001 |
| 0.3944 | 31.0 | 13578 | 0.4091 | 0.2065 | 0.1470 | 1.0120 | 0.3705 | 0.0001 |
| 0.3941 | 32.0 | 14016 | 0.4084 | 0.2060 | 0.1483 | 0.9708 | 0.3742 | 0.0001 |
| 0.3941 | 33.0 | 14454 | 0.4082 | 0.2057 | 0.1474 | 0.9317 | 0.3755 | 0.0001 |
| 0.3933 | 34.0 | 14892 | 0.4085 | 0.2061 | 0.1481 | 0.9619 | 0.3747 | 0.0001 |
| 0.3926 | 35.0 | 15330 | 0.4073 | 0.2054 | 0.1466 | 1.0523 | 0.3758 | 0.0001 |
| 0.3936 | 36.0 | 15768 | 0.4074 | 0.2052 | 0.1460 | 1.0622 | 0.3771 | 0.0001 |
| 0.3935 | 37.0 | 16206 | 0.4066 | 0.2047 | 0.1456 | 1.0201 | 0.3802 | 0.0001 |
| 0.3927 | 38.0 | 16644 | 0.4064 | 0.2045 | 0.1459 | 1.0557 | 0.3800 | 0.0001 |
| 0.392 | 39.0 | 17082 | 0.4078 | 0.2056 | 0.1469 | 1.0055 | 0.3771 | 0.0001 |
| 0.3915 | 40.0 | 17520 | 0.4068 | 0.2049 | 0.1464 | 0.9849 | 0.3805 | 0.0001 |
| 0.3915 | 41.0 | 17958 | 0.4089 | 0.2063 | 0.1489 | 0.8999 | 0.3778 | 0.0001 |
| 0.3907 | 42.0 | 18396 | 0.4069 | 0.2049 | 0.1463 | 1.0617 | 0.3797 | 0.0001 |
| 0.3919 | 43.0 | 18834 | 0.4058 | 0.2041 | 0.1450 | 1.0520 | 0.3830 | 0.0001 |
| 0.3902 | 44.0 | 19272 | 0.4071 | 0.2050 | 0.1475 | 1.0054 | 0.3809 | 0.0001 |
| 0.3896 | 45.0 | 19710 | 0.4067 | 0.2047 | 0.1440 | 1.1386 | 0.3813 | 0.0001 |
| 0.3925 | 46.0 | 20148 | 0.4067 | 0.2047 | 0.1457 | 1.0253 | 0.3831 | 0.0001 |
| 0.3896 | 47.0 | 20586 | 0.4062 | 0.2043 | 0.1473 | 1.0430 | 0.3834 | 0.0001 |
| 0.3902 | 48.0 | 21024 | 0.4065 | 0.2048 | 0.1457 | 1.1041 | 0.3812 | 0.0001 |
| 0.3902 | 49.0 | 21462 | 0.4071 | 0.2052 | 0.1463 | 1.0702 | 0.3798 | 0.0001 |
| 0.3897 | 50.0 | 21900 | 0.4064 | 0.2042 | 0.1479 | 0.8917 | 0.3857 | 1e-05 |
| 0.3875 | 51.0 | 22338 | 0.4058 | 0.2041 | 0.1437 | 0.9960 | 0.3845 | 1e-05 |
| 0.3874 | 52.0 | 22776 | 0.4053 | 0.2037 | 0.1446 | 1.0567 | 0.3851 | 1e-05 |
| 0.3899 | 53.0 | 23214 | 0.4056 | 0.2039 | 0.1462 | 1.0205 | 0.3859 | 1e-05 |
| 0.3892 | 54.0 | 23652 | 0.4059 | 0.2041 | 0.1441 | 0.9905 | 0.3854 | 1e-05 |
| 0.3892 | 55.0 | 24090 | 0.4061 | 0.2041 | 0.1471 | 0.9379 | 0.3856 | 1e-05 |
| 0.3869 | 56.0 | 24528 | 0.4059 | 0.2041 | 0.1454 | 0.9696 | 0.3854 | 1e-05 |
| 0.3869 | 57.0 | 24966 | 0.4058 | 0.2041 | 0.1460 | 1.0591 | 0.3842 | 1e-05 |
| 0.3874 | 58.0 | 25404 | 0.4063 | 0.2043 | 0.1460 | 0.9276 | 0.3860 | 1e-05 |
| 0.3887 | 59.0 | 25842 | 0.4056 | 0.2038 | 0.1453 | 0.9794 | 0.3868 | 0.0000 |
| 0.3882 | 60.0 | 26280 | 0.4057 | 0.2040 | 0.1446 | 1.0349 | 0.3851 | 0.0000 |
| 0.389 | 61.0 | 26718 | 0.4058 | 0.2041 | 0.1449 | 0.9860 | 0.3857 | 0.0000 |
| 0.3882 | 62.0 | 27156 | 0.4054 | 0.2037 | 0.1446 | 0.9528 | 0.3865 | 0.0000 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1
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