| --- |
| license: apache-2.0 |
| base_model: facebook/convnextv2-base-22k-384 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: convnext-base |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9442460317460317 |
| --- |
| |
| <!-- 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. --> |
|
|
| # convnext-base |
|
|
| This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2818 |
| - Accuracy: 0.9442 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.5947 | 1.0 | 1099 | 0.4242 | 0.8684 | |
| | 0.4798 | 2.0 | 2198 | 0.4242 | 0.8728 | |
| | 0.3625 | 3.0 | 3297 | 0.3553 | 0.9078 | |
| | 0.2777 | 4.0 | 4396 | 0.3241 | 0.9185 | |
| | 0.2368 | 5.0 | 5495 | 0.3413 | 0.9245 | |
| | 0.1635 | 6.0 | 6594 | 0.3116 | 0.9356 | |
| | 0.1564 | 7.0 | 7693 | 0.2997 | 0.9360 | |
| | 0.1082 | 8.0 | 8792 | 0.2916 | 0.9451 | |
| | 0.1146 | 9.0 | 9891 | 0.2963 | 0.9431 | |
| | 0.0801 | 10.0 | 10990 | 0.2946 | 0.9439 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.39.3 |
| - Pytorch 2.1.2 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
