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README.md
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---
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license: apache-2.0
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base_model: facebook/convnextv2-tiny-1k-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: convnext-tiny-upgrade-1k-224-batch-32
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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: 0.8850894632206759
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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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# convnext-tiny-upgrade-1k-224-batch-32
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This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4287
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- Accuracy: 0.8851
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.5523 | 1.0 | 550 | 1.2083 | 0.7010 |
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| 1.0852 | 2.0 | 1100 | 0.7955 | 0.7960 |
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| 0.9179 | 3.0 | 1650 | 0.6425 | 0.8258 |
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| 0.7621 | 4.0 | 2200 | 0.5426 | 0.8549 |
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| 0.7506 | 5.0 | 2750 | 0.5018 | 0.8624 |
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| 0.6774 | 6.0 | 3300 | 0.4792 | 0.8684 |
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| 0.6364 | 7.0 | 3850 | 0.4526 | 0.8744 |
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| 0.5961 | 8.0 | 4400 | 0.4362 | 0.8799 |
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| 0.602 | 9.0 | 4950 | 0.4316 | 0.8827 |
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| 0.5896 | 10.0 | 5500 | 0.4287 | 0.8851 |
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### Framework versions
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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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