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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/convnextv2-base-22k-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - image_folder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: convnextv2-base-22k-224-finetuned-hand_class
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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: image_folder
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+ type: image_folder
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+ config: default
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+ split: train
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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: 0.7336683417085427
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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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+ # convnextv2-base-22k-224-finetuned-hand_class
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the image_folder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5846
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+ - Accuracy: 0.7337
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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: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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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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+ | 0.6258 | 1.0 | 14 | 0.5879 | 0.7136 |
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+ | 0.5574 | 2.0 | 28 | 0.5707 | 0.7286 |
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+ | 0.5062 | 3.0 | 42 | 0.5633 | 0.7186 |
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+ | 0.4812 | 4.0 | 56 | 0.5761 | 0.7136 |
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+ | 0.4418 | 5.0 | 70 | 0.5644 | 0.7312 |
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+ | 0.4167 | 6.0 | 84 | 0.5756 | 0.7236 |
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+ | 0.4091 | 7.0 | 98 | 0.5751 | 0.7337 |
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+ | 0.379 | 8.0 | 112 | 0.5727 | 0.7312 |
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+ | 0.3717 | 9.0 | 126 | 0.5877 | 0.7387 |
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+ | 0.346 | 10.0 | 140 | 0.5846 | 0.7337 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3
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