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--- |
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license: apache-2.0 |
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base_model: facebook/dinov2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Dinotron |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Dinotron |
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This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0265 |
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- Accuracy: 0.9932 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 7 | 0.1146 | 0.9638 | |
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| 0.3773 | 2.0 | 14 | 0.0336 | 0.9932 | |
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| 0.0541 | 3.0 | 21 | 0.0402 | 0.9887 | |
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| 0.0541 | 4.0 | 28 | 0.0463 | 0.9887 | |
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| 0.0476 | 5.0 | 35 | 0.0594 | 0.9819 | |
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| 0.1408 | 6.0 | 42 | 0.1296 | 0.9570 | |
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| 0.1408 | 7.0 | 49 | 0.0872 | 0.9729 | |
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| 0.0898 | 8.0 | 56 | 0.2245 | 0.9344 | |
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| 0.216 | 9.0 | 63 | 0.1444 | 0.9570 | |
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| 0.076 | 10.0 | 70 | 0.0316 | 0.9887 | |
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| 0.076 | 11.0 | 77 | 0.0411 | 0.9864 | |
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| 0.0369 | 12.0 | 84 | 0.0275 | 0.9887 | |
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| 0.0505 | 13.0 | 91 | 0.1610 | 0.9638 | |
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| 0.0505 | 14.0 | 98 | 0.0513 | 0.9910 | |
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| 0.0274 | 15.0 | 105 | 0.2366 | 0.9615 | |
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| 0.0735 | 16.0 | 112 | 0.0738 | 0.9796 | |
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| 0.0735 | 17.0 | 119 | 0.0529 | 0.9819 | |
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| 0.0334 | 18.0 | 126 | 0.1024 | 0.9661 | |
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| 0.0347 | 19.0 | 133 | 0.0919 | 0.9819 | |
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| 0.0206 | 20.0 | 140 | 0.0851 | 0.9864 | |
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| 0.0206 | 21.0 | 147 | 0.1004 | 0.9796 | |
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| 0.0516 | 22.0 | 154 | 0.1706 | 0.9638 | |
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| 0.0418 | 23.0 | 161 | 0.0505 | 0.9910 | |
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| 0.0418 | 24.0 | 168 | 0.0939 | 0.9774 | |
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| 0.0173 | 25.0 | 175 | 0.0553 | 0.9842 | |
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| 0.0239 | 26.0 | 182 | 0.1255 | 0.9796 | |
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| 0.0239 | 27.0 | 189 | 0.2256 | 0.9661 | |
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| 0.0286 | 28.0 | 196 | 0.0943 | 0.9751 | |
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| 0.0502 | 29.0 | 203 | 0.0937 | 0.9751 | |
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| 0.0102 | 30.0 | 210 | 0.0910 | 0.9842 | |
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| 0.0102 | 31.0 | 217 | 0.0336 | 0.9887 | |
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| 0.0182 | 32.0 | 224 | 0.0870 | 0.9796 | |
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| 0.0126 | 33.0 | 231 | 0.0565 | 0.9842 | |
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| 0.0126 | 34.0 | 238 | 0.0541 | 0.9842 | |
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| 0.0157 | 35.0 | 245 | 0.0591 | 0.9932 | |
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| 0.0059 | 36.0 | 252 | 0.0985 | 0.9819 | |
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| 0.0059 | 37.0 | 259 | 0.0813 | 0.9819 | |
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| 0.0092 | 38.0 | 266 | 0.0239 | 0.9955 | |
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| 0.0225 | 39.0 | 273 | 0.0982 | 0.9706 | |
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| 0.0105 | 40.0 | 280 | 0.0113 | 0.9955 | |
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| 0.0105 | 41.0 | 287 | 0.0127 | 0.9977 | |
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| 0.007 | 42.0 | 294 | 0.0760 | 0.9887 | |
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| 0.0032 | 43.0 | 301 | 0.0196 | 0.9932 | |
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| 0.0032 | 44.0 | 308 | 0.0171 | 0.9932 | |
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| 0.0206 | 45.0 | 315 | 0.0501 | 0.9910 | |
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| 0.0001 | 46.0 | 322 | 0.0925 | 0.9842 | |
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| 0.0001 | 47.0 | 329 | 0.0318 | 0.9910 | |
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| 0.0017 | 48.0 | 336 | 0.0612 | 0.9864 | |
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| 0.0023 | 49.0 | 343 | 0.0685 | 0.9864 | |
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| 0.0013 | 50.0 | 350 | 0.0265 | 0.9932 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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