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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 |
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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: 0.9115079365079365 |
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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 |
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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: 0.4288 |
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- Accuracy: 0.9115 |
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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: 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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| 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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### 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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