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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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- image-classification |
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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: vuongnhathien/30VNFoods |
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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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<!-- 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-nano-20ep |
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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 vuongnhathien/30VNFoods 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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## 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: 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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### Training results |
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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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### 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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