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End of training

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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-patch16-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: hushem_40x_deit_tiny_f1
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8444444444444444
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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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+ # hushem_40x_deit_tiny_f1
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6177
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+ - Accuracy: 0.8444
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 10
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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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+ | 0.1057 | 1.0 | 107 | 0.4673 | 0.8222 |
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+ | 0.0156 | 2.0 | 214 | 0.4217 | 0.8667 |
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+ | 0.0006 | 2.99 | 321 | 0.3052 | 0.8889 |
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+ | 0.0004 | 4.0 | 429 | 0.7953 | 0.8222 |
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+ | 0.0004 | 5.0 | 536 | 0.2677 | 0.8667 |
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+ | 0.0001 | 6.0 | 643 | 0.5139 | 0.8444 |
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+ | 0.0 | 6.99 | 750 | 0.5825 | 0.8444 |
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+ | 0.0 | 8.0 | 858 | 0.6043 | 0.8444 |
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+ | 0.0 | 9.0 | 965 | 0.6155 | 0.8444 |
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+ | 0.0 | 9.98 | 1070 | 0.6177 | 0.8444 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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