| | --- |
| | license: apache-2.0 |
| | base_model: facebook/convnext-base-224-22k |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: idbwbase |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # idbwbase |
| |
|
| | This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the indian_food_images dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0978 |
| | - Accuracy: 0.9741 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.373 | 1.0 | 4709 | 0.3002 | 0.8705 | |
| | | 0.3244 | 2.0 | 9418 | 0.2262 | 0.9044 | |
| | | 0.2801 | 3.0 | 14127 | 0.1987 | 0.9196 | |
| | | 0.2366 | 4.0 | 18836 | 0.1788 | 0.9345 | |
| | | 0.2051 | 5.0 | 23545 | 0.1463 | 0.9484 | |
| | | 0.1764 | 6.0 | 28254 | 0.1202 | 0.9593 | |
| | | 0.1595 | 7.0 | 32963 | 0.1243 | 0.9655 | |
| | | 0.1359 | 8.0 | 37672 | 0.1188 | 0.9659 | |
| | | 0.1231 | 9.0 | 42381 | 0.0978 | 0.9741 | |
| | | 0.1162 | 10.0 | 47090 | 0.1001 | 0.9761 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.15.2 |
| |
|
