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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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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: vit-base-patch16-224-dmae-va-da2-40 |
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results: [] |
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datasets: |
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- Augusto777/dmae-ve-da2 |
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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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# vit-base-patch16-224-dmae-va-da2-40 |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co./google/vit-base-patch16-224) on [Augusto777/dmae-ve-da2](https://huggingface.co./datasets/Augusto777/dmae-ve-da2) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2660 |
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- Accuracy: 0.9655 |
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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: 40 |
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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 | 0.94 | 4 | 1.2931 | 0.4310 | |
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| No log | 1.88 | 8 | 1.2024 | 0.5517 | |
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| 1.2651 | 2.82 | 12 | 0.9896 | 0.6552 | |
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| 1.2651 | 4.0 | 17 | 0.7972 | 0.7241 | |
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| 1.2651 | 4.94 | 21 | 0.7336 | 0.6552 | |
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| 0.7523 | 5.88 | 25 | 0.5781 | 0.8103 | |
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| 0.7523 | 6.82 | 29 | 0.4912 | 0.8793 | |
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| 0.7523 | 8.0 | 34 | 0.4112 | 0.9138 | |
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| 0.4209 | 8.94 | 38 | 0.3383 | 0.9138 | |
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| 0.4209 | 9.88 | 42 | 0.3129 | 0.9483 | |
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| 0.4209 | 10.82 | 46 | 0.2660 | 0.9655 | |
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| 0.2647 | 12.0 | 51 | 0.3184 | 0.9310 | |
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| 0.2647 | 12.94 | 55 | 0.2871 | 0.9310 | |
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| 0.2647 | 13.88 | 59 | 0.2766 | 0.9138 | |
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| 0.1743 | 14.82 | 63 | 0.2727 | 0.8966 | |
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| 0.1743 | 16.0 | 68 | 0.2282 | 0.9310 | |
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| 0.1511 | 16.94 | 72 | 0.2892 | 0.8966 | |
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| 0.1511 | 17.88 | 76 | 0.2482 | 0.8966 | |
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| 0.1511 | 18.82 | 80 | 0.2363 | 0.9310 | |
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| 0.1253 | 20.0 | 85 | 0.1622 | 0.9483 | |
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| 0.1253 | 20.94 | 89 | 0.1753 | 0.9483 | |
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| 0.1253 | 21.88 | 93 | 0.1593 | 0.9655 | |
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| 0.087 | 22.82 | 97 | 0.1334 | 0.9483 | |
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| 0.087 | 24.0 | 102 | 0.1088 | 0.9483 | |
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| 0.087 | 24.94 | 106 | 0.1130 | 0.9483 | |
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| 0.0856 | 25.88 | 110 | 0.1459 | 0.9138 | |
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| 0.0856 | 26.82 | 114 | 0.1445 | 0.9655 | |
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| 0.0856 | 28.0 | 119 | 0.1234 | 0.9655 | |
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| 0.081 | 28.94 | 123 | 0.1224 | 0.9483 | |
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| 0.081 | 29.88 | 127 | 0.1303 | 0.9483 | |
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| 0.081 | 30.82 | 131 | 0.1372 | 0.9483 | |
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| 0.0554 | 32.0 | 136 | 0.1421 | 0.9483 | |
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| 0.0554 | 32.94 | 140 | 0.1307 | 0.9483 | |
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| 0.0783 | 33.88 | 144 | 0.1244 | 0.9483 | |
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| 0.0783 | 34.82 | 148 | 0.1195 | 0.9483 | |
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| 0.0783 | 36.0 | 153 | 0.1171 | 0.9483 | |
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| 0.0646 | 36.94 | 157 | 0.1165 | 0.9483 | |
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| 0.0646 | 37.65 | 160 | 0.1163 | 0.9483 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
