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Ziboiai-large-2024_10_31-prova_batch-size32_freeze_probs

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dinov2
multilabel-image-classification
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Ziboiai-large-2024_10_31-prova_batch-size32_freeze_probs / README.md
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Evaluation on the test set completed on 2024_10_31.
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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-large
tags:
  - generated_from_trainer
model-index:
  - name: Ziboiai-large-2024_10_31-prova_batch-size32_freeze_probs
    results: []

Ziboiai-large-2024_10_31-prova_batch-size32_freeze_probs

This model is a fine-tuned version of facebook/dinov2-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6195
  • Rmse: 0.3419
  • Mae: 0.3068
  • R2: -1.6131
  • Explained Variance: 0.2071
  • Learning Rate: 1e-05

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: 32
  • eval_batch_size: 32
  • 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 R2 Explained Variance Rate
No log 1.0 2 0.7150 0.4100 0.3849 -20.2909 0.0364 0.001
No log 2.0 4 0.7314 0.4163 0.3895 -21.2182 0.0241 0.001
No log 3.0 6 0.7726 0.4321 0.4041 -24.8224 -0.0469 0.001
No log 4.0 8 0.7917 0.4380 0.4095 -26.5816 -0.0667 0.001
No log 5.0 10 0.7853 0.4318 0.4021 -26.9559 -0.1362 0.001
No log 6.0 12 0.7648 0.4224 0.3905 -24.4015 -0.1297 0.001
No log 7.0 14 0.7392 0.4103 0.3760 -22.5579 -0.1098 0.001
No log 8.0 16 0.7115 0.3983 0.3639 -20.0674 -0.1054 0.0001
No log 9.0 18 0.6897 0.3879 0.3535 -18.1665 -0.0925 0.0001
No log 10.0 20 0.6777 0.3818 0.3468 -16.9447 -0.1029 0.0001
No log 11.0 22 0.6702 0.3780 0.3424 -16.0375 -0.1169 0.0001
No log 12.0 24 0.6639 0.3744 0.3389 -15.6052 -0.1121 0.0001
No log 13.0 26 0.6565 0.3703 0.3346 -14.8051 -0.1065 0.0001
No log 14.0 28 0.6501 0.3668 0.3310 -14.2312 -0.0958 0.0001
No log 15.0 30 0.6468 0.3648 0.3289 -14.0799 -0.0855 0.0001
No log 16.0 32 0.6471 0.3650 0.3289 -14.2557 -0.0823 0.0001
No log 17.0 34 0.6435 0.3631 0.3268 -14.0598 -0.0810 0.0001
No log 18.0 36 0.6438 0.3634 0.3270 -14.0369 -0.0799 0.0001
No log 19.0 38 0.6400 0.3614 0.3250 -13.8152 -0.0888 0.0001
No log 20.0 40 0.6392 0.3609 0.3246 -13.7104 -0.0935 0.0001
No log 21.0 42 0.6387 0.3606 0.3246 -13.8099 -0.0993 0.0001
No log 22.0 44 0.6388 0.3606 0.3243 -13.8497 -0.1056 0.0001
No log 23.0 46 0.6362 0.3590 0.3228 -13.5622 -0.1035 0.0001
No log 24.0 48 0.6354 0.3585 0.3223 -13.6453 -0.1058 0.0001
No log 25.0 50 0.6345 0.3578 0.3214 -13.6023 -0.1036 0.0001
No log 26.0 52 0.6349 0.3581 0.3212 -13.6304 -0.1173 0.0001
No log 27.0 54 0.6333 0.3571 0.3201 -13.5613 -0.1148 0.0001
No log 28.0 56 0.6295 0.3548 0.3177 -13.2331 -0.1083 0.0001
No log 29.0 58 0.6285 0.3543 0.3173 -13.1623 -0.1047 0.0001
No log 30.0 60 0.6263 0.3532 0.3163 -12.7132 -0.0926 0.0001
No log 31.0 62 0.6273 0.3538 0.3167 -12.8739 -0.0893 0.0001
No log 32.0 64 0.6294 0.3550 0.3181 -12.9355 -0.0790 0.0001
No log 33.0 66 0.6299 0.3554 0.3185 -12.9352 -0.0752 0.0001
No log 34.0 68 0.6321 0.3564 0.3193 -13.2672 -0.0702 0.0001
No log 35.0 70 0.6279 0.3541 0.3175 -12.9995 -0.0487 0.0001
No log 36.0 72 0.6280 0.3541 0.3174 -13.0074 -0.0466 0.0001
No log 37.0 74 0.6304 0.3554 0.3187 -13.2310 -0.0494 1e-05
No log 38.0 76 0.6297 0.3551 0.3183 -12.9830 -0.0439 1e-05
No log 39.0 78 0.6308 0.3558 0.3193 -13.1598 -0.0430 1e-05
No log 40.0 80 0.6292 0.3548 0.3183 -13.0698 -0.0435 1e-05

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1