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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-22k-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- image_folder |
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metrics: |
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- accuracy |
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model-index: |
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- name: convnextv2-base-22k-224-finetuned-hand_class |
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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: image_folder |
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type: image_folder |
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config: default |
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split: train |
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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: 0.7336683417085427 |
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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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# convnextv2-base-22k-224-finetuned-hand_class |
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This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5846 |
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- Accuracy: 0.7337 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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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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| 0.6258 | 1.0 | 14 | 0.5879 | 0.7136 | |
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| 0.5574 | 2.0 | 28 | 0.5707 | 0.7286 | |
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| 0.5062 | 3.0 | 42 | 0.5633 | 0.7186 | |
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| 0.4812 | 4.0 | 56 | 0.5761 | 0.7136 | |
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| 0.4418 | 5.0 | 70 | 0.5644 | 0.7312 | |
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| 0.4167 | 6.0 | 84 | 0.5756 | 0.7236 | |
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| 0.4091 | 7.0 | 98 | 0.5751 | 0.7337 | |
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| 0.379 | 8.0 | 112 | 0.5727 | 0.7312 | |
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| 0.3717 | 9.0 | 126 | 0.5877 | 0.7387 | |
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| 0.346 | 10.0 | 140 | 0.5846 | 0.7337 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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