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# Amoros_Beaugosse_batch_64_epochs_200_test-large-2025_05_26_67930-bs64_freeze

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: 0.0806
- F1 Micro: 0.6521
- F1 Macro: 0.5228
- Accuracy: 0.5581
- 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1 Micro | F1 Macro | Accuracy | Rate   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|:------:|
| No log        | 1.0   | 489   | 0.1057          | 0.4791   | 0.1939   | 0.3399   | 0.001  |
| 0.2268        | 2.0   | 978   | 0.0992          | 0.5171   | 0.2748   | 0.3829   | 0.001  |
| 0.1131        | 3.0   | 1467  | 0.0967          | 0.5206   | 0.3019   | 0.3833   | 0.001  |
| 0.1072        | 4.0   | 1956  | 0.0958          | 0.5299   | 0.3230   | 0.3974   | 0.001  |
| 0.1049        | 5.0   | 2445  | 0.0957          | 0.5463   | 0.3499   | 0.4164   | 0.001  |
| 0.1038        | 6.0   | 2934  | 0.0949          | 0.5293   | 0.3454   | 0.3913   | 0.001  |
| 0.1041        | 7.0   | 3423  | 0.0951          | 0.5530   | 0.3660   | 0.4262   | 0.001  |
| 0.1035        | 8.0   | 3912  | 0.0956          | 0.5493   | 0.3504   | 0.4249   | 0.001  |
| 0.1028        | 9.0   | 4401  | 0.0945          | 0.5652   | 0.3616   | 0.4453   | 0.001  |
| 0.1029        | 10.0  | 4890  | 0.0934          | 0.5579   | 0.3733   | 0.4259   | 0.001  |
| 0.1037        | 11.0  | 5379  | 0.0938          | 0.5515   | 0.3631   | 0.4218   | 0.001  |
| 0.1026        | 12.0  | 5868  | 0.0932          | 0.5646   | 0.3631   | 0.4364   | 0.001  |
| 0.1024        | 13.0  | 6357  | 0.0923          | 0.5593   | 0.3755   | 0.4256   | 0.001  |
| 0.1025        | 14.0  | 6846  | 0.0913          | 0.5802   | 0.3898   | 0.4561   | 0.001  |
| 0.1012        | 15.0  | 7335  | 0.0920          | 0.5718   | 0.3889   | 0.4462   | 0.001  |
| 0.1016        | 16.0  | 7824  | 0.0916          | 0.5697   | 0.3873   | 0.4455   | 0.001  |
| 0.1016        | 17.0  | 8313  | 0.0931          | 0.5598   | 0.3802   | 0.4297   | 0.001  |
| 0.102         | 18.0  | 8802  | 0.0925          | 0.5640   | 0.3654   | 0.4359   | 0.001  |
| 0.1017        | 19.0  | 9291  | 0.0914          | 0.5738   | 0.3874   | 0.4467   | 0.001  |
| 0.1019        | 20.0  | 9780  | 0.0917          | 0.5687   | 0.3728   | 0.4417   | 0.001  |
| 0.1006        | 21.0  | 10269 | 0.0881          | 0.5932   | 0.4237   | 0.4712   | 0.0001 |
| 0.0968        | 22.0  | 10758 | 0.0870          | 0.6013   | 0.4384   | 0.4823   | 0.0001 |
| 0.0946        | 23.0  | 11247 | 0.0866          | 0.6039   | 0.4367   | 0.4853   | 0.0001 |
| 0.0942        | 24.0  | 11736 | 0.0861          | 0.6062   | 0.4452   | 0.4893   | 0.0001 |
| 0.0938        | 25.0  | 12225 | 0.0854          | 0.6100   | 0.4490   | 0.4926   | 0.0001 |
| 0.0929        | 26.0  | 12714 | 0.0853          | 0.6145   | 0.4482   | 0.5026   | 0.0001 |
| 0.0921        | 27.0  | 13203 | 0.0851          | 0.6144   | 0.4441   | 0.4999   | 0.0001 |
| 0.0917        | 28.0  | 13692 | 0.0845          | 0.6152   | 0.4457   | 0.5013   | 0.0001 |
| 0.0913        | 29.0  | 14181 | 0.0846          | 0.6143   | 0.4484   | 0.4990   | 0.0001 |
| 0.0916        | 30.0  | 14670 | 0.0843          | 0.6204   | 0.4621   | 0.5092   | 0.0001 |
| 0.0911        | 31.0  | 15159 | 0.0841          | 0.6214   | 0.4646   | 0.5116   | 0.0001 |
| 0.0901        | 32.0  | 15648 | 0.0839          | 0.6225   | 0.4649   | 0.5123   | 0.0001 |
| 0.0904        | 33.0  | 16137 | 0.0837          | 0.6267   | 0.4654   | 0.5180   | 0.0001 |
| 0.0898        | 34.0  | 16626 | 0.0834          | 0.6241   | 0.4665   | 0.5132   | 0.0001 |
| 0.089         | 35.0  | 17115 | 0.0834          | 0.6271   | 0.4762   | 0.5179   | 0.0001 |
| 0.0894        | 36.0  | 17604 | 0.0832          | 0.6244   | 0.4721   | 0.5158   | 0.0001 |
| 0.0891        | 37.0  | 18093 | 0.0831          | 0.6264   | 0.4712   | 0.5174   | 0.0001 |
| 0.0891        | 38.0  | 18582 | 0.0832          | 0.6288   | 0.4690   | 0.5194   | 0.0001 |
| 0.0889        | 39.0  | 19071 | 0.0828          | 0.6318   | 0.4810   | 0.5250   | 0.0001 |
| 0.0885        | 40.0  | 19560 | 0.0826          | 0.6316   | 0.4825   | 0.5232   | 0.0001 |
| 0.0876        | 41.0  | 20049 | 0.0827          | 0.6268   | 0.4703   | 0.5165   | 0.0001 |
| 0.0877        | 42.0  | 20538 | 0.0822          | 0.6324   | 0.4893   | 0.5240   | 0.0001 |
| 0.0879        | 43.0  | 21027 | 0.0819          | 0.6371   | 0.5045   | 0.5321   | 0.0001 |
| 0.0877        | 44.0  | 21516 | 0.0825          | 0.6295   | 0.4782   | 0.5218   | 0.0001 |
| 0.0867        | 45.0  | 22005 | 0.0824          | 0.6305   | 0.4814   | 0.5237   | 0.0001 |
| 0.0867        | 46.0  | 22494 | 0.0821          | 0.6324   | 0.4893   | 0.5245   | 0.0001 |
| 0.0873        | 47.0  | 22983 | 0.0818          | 0.6362   | 0.4933   | 0.5308   | 0.0001 |
| 0.0868        | 48.0  | 23472 | 0.0817          | 0.6393   | 0.4984   | 0.5357   | 0.0001 |
| 0.0868        | 49.0  | 23961 | 0.0821          | 0.6329   | 0.4864   | 0.5260   | 0.0001 |
| 0.0865        | 50.0  | 24450 | 0.0819          | 0.6332   | 0.4850   | 0.5254   | 0.0001 |
| 0.0869        | 51.0  | 24939 | 0.0817          | 0.6373   | 0.4914   | 0.5332   | 0.0001 |
| 0.0865        | 52.0  | 25428 | 0.0821          | 0.6343   | 0.5013   | 0.5295   | 0.0001 |
| 0.0863        | 53.0  | 25917 | 0.0815          | 0.6403   | 0.4996   | 0.5375   | 0.0001 |
| 0.0862        | 54.0  | 26406 | 0.0818          | 0.6374   | 0.4899   | 0.5323   | 0.0001 |
| 0.086         | 55.0  | 26895 | 0.0818          | 0.6326   | 0.4935   | 0.5249   | 0.0001 |
| 0.086         | 56.0  | 27384 | 0.0816          | 0.6393   | 0.4962   | 0.5364   | 0.0001 |
| 0.0854        | 57.0  | 27873 | 0.0817          | 0.6391   | 0.4981   | 0.5363   | 0.0001 |
| 0.0856        | 58.0  | 28362 | 0.0815          | 0.6428   | 0.4922   | 0.5402   | 0.0001 |
| 0.0856        | 59.0  | 28851 | 0.0814          | 0.6360   | 0.4918   | 0.5308   | 0.0001 |
| 0.0852        | 60.0  | 29340 | 0.0813          | 0.6472   | 0.5072   | 0.5491   | 0.0001 |
| 0.0852        | 61.0  | 29829 | 0.0816          | 0.6377   | 0.4847   | 0.5339   | 0.0001 |
| 0.0845        | 62.0  | 30318 | 0.0810          | 0.6401   | 0.4960   | 0.5367   | 0.0001 |
| 0.0851        | 63.0  | 30807 | 0.0814          | 0.6433   | 0.4912   | 0.5433   | 0.0001 |
| 0.0847        | 64.0  | 31296 | 0.0810          | 0.6383   | 0.4912   | 0.5330   | 0.0001 |
| 0.0851        | 65.0  | 31785 | 0.0808          | 0.6409   | 0.5117   | 0.5383   | 0.0001 |
| 0.0841        | 66.0  | 32274 | 0.0807          | 0.6437   | 0.4995   | 0.5417   | 0.0001 |
| 0.0841        | 67.0  | 32763 | 0.0808          | 0.6439   | 0.5073   | 0.5435   | 0.0001 |
| 0.0842        | 68.0  | 33252 | 0.0809          | 0.6405   | 0.5073   | 0.5369   | 0.0001 |
| 0.0843        | 69.0  | 33741 | 0.0810          | 0.6391   | 0.4926   | 0.5361   | 0.0001 |
| 0.0839        | 70.0  | 34230 | 0.0806          | 0.6425   | 0.5095   | 0.5428   | 0.0001 |
| 0.0843        | 71.0  | 34719 | 0.0809          | 0.6404   | 0.5159   | 0.5360   | 0.0001 |
| 0.0838        | 72.0  | 35208 | 0.0813          | 0.6470   | 0.5043   | 0.5485   | 0.0001 |
| 0.0836        | 73.0  | 35697 | 0.0804          | 0.6405   | 0.5029   | 0.5349   | 0.0001 |
| 0.084         | 74.0  | 36186 | 0.0806          | 0.6441   | 0.5028   | 0.5432   | 0.0001 |
| 0.0836        | 75.0  | 36675 | 0.0807          | 0.6421   | 0.5134   | 0.5387   | 0.0001 |
| 0.0831        | 76.0  | 37164 | 0.0805          | 0.6427   | 0.5133   | 0.5408   | 0.0001 |
| 0.0838        | 77.0  | 37653 | 0.0806          | 0.6467   | 0.5015   | 0.5474   | 0.0001 |
| 0.0827        | 78.0  | 38142 | 0.0808          | 0.6402   | 0.4998   | 0.5396   | 0.0001 |
| 0.0833        | 79.0  | 38631 | 0.0805          | 0.6475   | 0.5048   | 0.5496   | 0.0001 |
| 0.0821        | 80.0  | 39120 | 0.0798          | 0.6531   | 0.5148   | 0.5560   | 1e-05  |
| 0.0814        | 81.0  | 39609 | 0.0796          | 0.6533   | 0.5242   | 0.5555   | 1e-05  |
| 0.081         | 82.0  | 40098 | 0.0795          | 0.6568   | 0.5260   | 0.5633   | 1e-05  |
| 0.0808        | 83.0  | 40587 | 0.0794          | 0.6562   | 0.5293   | 0.5608   | 1e-05  |
| 0.0802        | 84.0  | 41076 | 0.0792          | 0.6567   | 0.5257   | 0.5616   | 1e-05  |
| 0.0807        | 85.0  | 41565 | 0.0794          | 0.6577   | 0.5262   | 0.5621   | 1e-05  |
| 0.0799        | 86.0  | 42054 | 0.0794          | 0.6569   | 0.5265   | 0.5616   | 1e-05  |
| 0.0801        | 87.0  | 42543 | 0.0794          | 0.6570   | 0.5198   | 0.5627   | 1e-05  |
| 0.0803        | 88.0  | 43032 | 0.0794          | 0.6571   | 0.5282   | 0.5642   | 1e-05  |
| 0.0801        | 89.0  | 43521 | 0.0794          | 0.6551   | 0.5200   | 0.5597   | 1e-05  |
| 0.0799        | 90.0  | 44010 | 0.0794          | 0.6550   | 0.5186   | 0.5598   | 1e-05  |
| 0.0799        | 91.0  | 44499 | 0.0793          | 0.6558   | 0.5292   | 0.5622   | 0.0000 |
| 0.0799        | 92.0  | 44988 | 0.0793          | 0.6554   | 0.5248   | 0.5610   | 0.0000 |
| 0.0799        | 93.0  | 45477 | 0.0794          | 0.6563   | 0.5230   | 0.5609   | 0.0000 |
| 0.0797        | 94.0  | 45966 | 0.0794          | 0.6533   | 0.5214   | 0.5572   | 0.0000 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.6.0+cu118
- Datasets 3.0.2
- Tokenizers 0.21.1

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