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vit-base-patch16-224-dmae-va-U3-40A

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  1. README.md +102 -0
  2. model.safetensors +1 -1
  3. runs/Mar11_00-37-16_89e2f3456c0c/events.out.tfevents.1710117447.89e2f3456c0c.2146.0 +2 -2
README.md ADDED
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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-U3-40A
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+ results: []
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+ ---
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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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+
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+ # vit-base-patch16-224-dmae-va-U3-40A
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+
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0110
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+ - Accuracy: 1.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 7 | 1.3292 | 0.3737 |
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+ | 1.3407 | 2.0 | 14 | 1.1079 | 0.5152 |
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+ | 1.3407 | 3.0 | 21 | 0.8918 | 0.6263 |
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+ | 0.9919 | 4.0 | 28 | 0.6447 | 0.7879 |
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+ | 0.9919 | 5.0 | 35 | 0.4502 | 0.8283 |
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+ | 0.5761 | 6.0 | 42 | 0.2720 | 0.9192 |
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+ | 0.3111 | 7.0 | 49 | 0.2302 | 0.9293 |
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+ | 0.3111 | 8.0 | 56 | 0.1650 | 0.9495 |
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+ | 0.204 | 9.0 | 63 | 0.1503 | 0.9495 |
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+ | 0.204 | 10.0 | 70 | 0.0814 | 0.9798 |
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+ | 0.1518 | 11.0 | 77 | 0.0604 | 0.9798 |
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+ | 0.1272 | 12.0 | 84 | 0.1265 | 0.9495 |
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+ | 0.1272 | 13.0 | 91 | 0.0518 | 0.9798 |
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+ | 0.1379 | 14.0 | 98 | 0.0448 | 0.9899 |
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+ | 0.1379 | 15.0 | 105 | 0.0361 | 0.9899 |
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+ | 0.092 | 16.0 | 112 | 0.0322 | 0.9899 |
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+ | 0.092 | 17.0 | 119 | 0.0213 | 1.0 |
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+ | 0.0762 | 18.0 | 126 | 0.0469 | 0.9899 |
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+ | 0.0954 | 19.0 | 133 | 0.0615 | 0.9899 |
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+ | 0.0954 | 20.0 | 140 | 0.0313 | 0.9899 |
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+ | 0.0795 | 21.0 | 147 | 0.0381 | 0.9899 |
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+ | 0.0795 | 22.0 | 154 | 0.0138 | 1.0 |
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+ | 0.077 | 23.0 | 161 | 0.0170 | 1.0 |
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+ | 0.0675 | 24.0 | 168 | 0.0107 | 1.0 |
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+ | 0.0675 | 25.0 | 175 | 0.0193 | 0.9899 |
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+ | 0.0659 | 26.0 | 182 | 0.0255 | 0.9899 |
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+ | 0.0659 | 27.0 | 189 | 0.0201 | 0.9899 |
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+ | 0.0758 | 28.0 | 196 | 0.0325 | 0.9899 |
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+ | 0.0758 | 29.0 | 203 | 0.0110 | 1.0 |
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+ | 0.0589 | 30.0 | 210 | 0.0159 | 1.0 |
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+ | 0.0521 | 31.0 | 217 | 0.0319 | 0.9899 |
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+ | 0.0521 | 32.0 | 224 | 0.0294 | 0.9798 |
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+ | 0.0618 | 33.0 | 231 | 0.0392 | 0.9798 |
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+ | 0.0618 | 34.0 | 238 | 0.0269 | 0.9899 |
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+ | 0.0422 | 35.0 | 245 | 0.0210 | 0.9899 |
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+ | 0.0551 | 36.0 | 252 | 0.0178 | 0.9899 |
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+ | 0.0551 | 37.0 | 259 | 0.0159 | 0.9899 |
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+ | 0.0518 | 38.0 | 266 | 0.0124 | 0.9899 |
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+ | 0.0518 | 39.0 | 273 | 0.0112 | 1.0 |
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+ | 0.0313 | 40.0 | 280 | 0.0110 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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