| | --- |
| | license: apache-2.0 |
| | base_model: facebook/convnextv2-tiny-22k-384 |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: ConvnextV2-base |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: vuongnhathien/30VNFoods |
| | type: imagefolder |
| | config: default |
| | split: validation |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9192460317460317 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # ConvnextV2-base |
| |
|
| | This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the vuongnhathien/30VNFoods dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4650 |
| | - Accuracy: 0.9192 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0003 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.5453 | 1.0 | 550 | 0.5385 | 0.8465 | |
| | | 0.3201 | 2.0 | 1100 | 0.5494 | 0.8465 | |
| | | 0.1818 | 3.0 | 1650 | 0.4973 | 0.8732 | |
| | | 0.0974 | 4.0 | 2200 | 0.5644 | 0.8652 | |
| | | 0.059 | 5.0 | 2750 | 0.5624 | 0.8891 | |
| | | 0.0371 | 6.0 | 3300 | 0.6428 | 0.8755 | |
| | | 0.0118 | 7.0 | 3850 | 0.5426 | 0.9026 | |
| | | 0.0169 | 8.0 | 4400 | 0.4927 | 0.9161 | |
| | | 0.0103 | 9.0 | 4950 | 0.5011 | 0.9105 | |
| | | 0.0017 | 10.0 | 5500 | 0.4820 | 0.9165 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.39.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| |
|
