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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-nano-22k-384
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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: convnext-nano-20ep
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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: validation
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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: 0.8702380952380953
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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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+ # convnext-nano-20ep
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4812
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+ - Accuracy: 0.8702
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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: 0.0003
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+ - train_batch_size: 64
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+ - eval_batch_size: 16
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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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+ - num_epochs: 20
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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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+ | 0.5831 | 1.0 | 275 | 0.5660 | 0.8278 |
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+ | 0.3159 | 2.0 | 550 | 0.5093 | 0.8529 |
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+ | 0.1892 | 3.0 | 825 | 0.4719 | 0.8779 |
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+ | 0.1111 | 4.0 | 1100 | 0.5067 | 0.8755 |
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+ | 0.0886 | 5.0 | 1375 | 0.5278 | 0.8708 |
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+ | 0.0697 | 6.0 | 1650 | 0.6000 | 0.8628 |
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+ | 0.0396 | 7.0 | 1925 | 0.6158 | 0.8736 |
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+ | 0.0386 | 8.0 | 2200 | 0.6448 | 0.8684 |
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+ | 0.0323 | 9.0 | 2475 | 0.5637 | 0.8915 |
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+ | 0.0157 | 10.0 | 2750 | 0.5845 | 0.8958 |
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+ | 0.0067 | 11.0 | 3025 | 0.5574 | 0.9018 |
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+ | 0.005 | 12.0 | 3300 | 0.5378 | 0.9034 |
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+ | 0.0031 | 13.0 | 3575 | 0.5526 | 0.9014 |
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+ | 0.0023 | 14.0 | 3850 | 0.5419 | 0.9093 |
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+ | 0.0026 | 15.0 | 4125 | 0.5323 | 0.9113 |
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+ | 0.0024 | 16.0 | 4400 | 0.5298 | 0.9117 |
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+ | 0.0019 | 17.0 | 4675 | 0.5323 | 0.9121 |
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+ | 0.002 | 18.0 | 4950 | 0.5315 | 0.9125 |
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+ | 0.0012 | 19.0 | 5225 | 0.5314 | 0.9121 |
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+ | 0.0019 | 20.0 | 5500 | 0.5315 | 0.9117 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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