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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
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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: 0.9115079365079365
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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
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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: 0.4288
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+ - Accuracy: 0.9115
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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: 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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+ | 0.6173 | 1.0 | 275 | 0.5020 | 0.8473 |
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+ | 0.3079 | 2.0 | 550 | 0.4532 | 0.8672 |
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+ | 0.174 | 3.0 | 825 | 0.4498 | 0.8771 |
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+ | 0.0955 | 4.0 | 1100 | 0.4480 | 0.8907 |
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+ | 0.0435 | 5.0 | 1375 | 0.4689 | 0.8938 |
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+ | 0.0282 | 6.0 | 1650 | 0.4556 | 0.9002 |
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+ | 0.0085 | 7.0 | 1925 | 0.3986 | 0.9161 |
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+ | 0.0065 | 8.0 | 2200 | 0.4051 | 0.9189 |
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+ | 0.0012 | 9.0 | 2475 | 0.4022 | 0.9221 |
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+ | 0.0023 | 10.0 | 2750 | 0.4029 | 0.9217 |
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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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