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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: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
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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: 1_lakh_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned
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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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+ # 1_lakh_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned
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+
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+ This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.4853
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+ - Accuracy: 0.3370
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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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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+ | 1.5715 | 1.0000 | 6051 | 2.0155 | 0.2758 |
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+ | 1.6433 | 1.9999 | 12102 | 2.2641 | 0.2734 |
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+ | 1.6866 | 2.9999 | 18153 | 2.1140 | 0.2888 |
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+ | 1.5693 | 4.0 | 24205 | 2.2003 | 0.3066 |
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+ | 1.5371 | 5.0000 | 30256 | 2.2069 | 0.2968 |
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+ | 1.4969 | 5.9999 | 36307 | 2.1547 | 0.3296 |
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+ | 1.4368 | 6.9999 | 42358 | 2.2579 | 0.3250 |
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+ | 1.3077 | 8.0 | 48410 | 2.2327 | 0.3360 |
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+ | 1.3775 | 9.0000 | 54461 | 2.3860 | 0.3400 |
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+ | 1.3595 | 9.9996 | 60510 | 2.4853 | 0.3370 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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