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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-tiny-distilled-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: quickdraw-DeiT-tiny-c
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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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+ # quickdraw-DeiT-tiny-c
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-distilled-patch16-224](https://huggingface.co/facebook/deit-tiny-distilled-patch16-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8784
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+ - Accuracy: 0.7849
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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: 0.0008
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+ - train_batch_size: 512
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+ - eval_batch_size: 512
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 10000
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+ - num_epochs: 8
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+ - mixed_precision_training: Native AMP
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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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+ | 1.2697 | 0.5688 | 5000 | 1.2368 | 0.6883 |
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+ | 1.1262 | 1.1377 | 10000 | 1.1299 | 0.7127 |
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+ | 1.0215 | 1.7065 | 15000 | 1.0110 | 0.7403 |
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+ | 0.939 | 2.2753 | 20000 | 0.9628 | 0.7521 |
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+ | 0.9129 | 2.8441 | 25000 | 0.9281 | 0.7606 |
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+ | 0.8507 | 3.4130 | 30000 | 0.8973 | 0.7687 |
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+ | 0.8354 | 3.9818 | 35000 | 0.8696 | 0.7752 |
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+ | 0.7773 | 4.5506 | 40000 | 0.8575 | 0.7791 |
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+ | 0.7011 | 5.1195 | 45000 | 0.8497 | 0.7829 |
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+ | 0.6989 | 5.6883 | 50000 | 0.8350 | 0.7860 |
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+ | 0.624 | 6.2571 | 55000 | 0.8524 | 0.7857 |
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+ | 0.6245 | 6.8259 | 60000 | 0.8499 | 0.7874 |
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+ | 0.565 | 7.3948 | 65000 | 0.8795 | 0.7849 |
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+ | 0.5663 | 7.9636 | 70000 | 0.8784 | 0.7849 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.2.1
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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