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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-22k-384 |
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tags: |
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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-base-8e-5 |
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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: imagefolder |
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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: 0.942063492063492 |
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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-base-8e-5 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2713 |
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- Accuracy: 0.9421 |
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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: 8e-05 |
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- train_batch_size: 16 |
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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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| 0.5312 | 1.0 | 1099 | 0.4722 | 0.8569 | |
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| 0.4064 | 2.0 | 2198 | 0.3651 | 0.9026 | |
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| 0.318 | 3.0 | 3297 | 0.3260 | 0.9145 | |
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| 0.2725 | 4.0 | 4396 | 0.3165 | 0.9197 | |
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| 0.212 | 5.0 | 5495 | 0.3330 | 0.9256 | |
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| 0.1711 | 6.0 | 6594 | 0.3273 | 0.9276 | |
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| 0.1552 | 7.0 | 7693 | 0.2993 | 0.9304 | |
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| 0.1039 | 8.0 | 8792 | 0.2773 | 0.9419 | |
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| 0.0996 | 9.0 | 9891 | 0.2786 | 0.9459 | |
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| 0.0765 | 10.0 | 10990 | 0.2780 | 0.9475 | |
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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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