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--- |
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license: apache-2.0 |
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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-large-224-22k-1k-convnext_bottom |
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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: 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: 0.9981447124304267 |
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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-large-224-22k-1k-convnext_bottom |
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This model is a fine-tuned version of [facebook/convnext-large-224-22k-1k](https://huggingface.co/facebook/convnext-large-224-22k-1k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0064 |
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- Accuracy: 0.9981 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 7 |
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- total_train_batch_size: 56 |
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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: 0.01 |
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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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| 0.0899 | 0.99 | 86 | 0.0290 | 0.9852 | |
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| 0.0651 | 2.0 | 173 | 0.0217 | 0.9889 | |
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| 0.0364 | 2.99 | 259 | 0.0170 | 0.9944 | |
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| 0.0678 | 4.0 | 346 | 0.0135 | 0.9963 | |
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| 0.0129 | 4.99 | 432 | 0.0120 | 0.9944 | |
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| 0.0189 | 6.0 | 519 | 0.0095 | 0.9944 | |
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| 0.0399 | 7.0 | 606 | 0.0098 | 0.9944 | |
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| 0.029 | 7.99 | 692 | 0.0121 | 0.9963 | |
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| 0.0153 | 9.0 | 779 | 0.0068 | 0.9981 | |
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| 0.0252 | 9.93 | 860 | 0.0064 | 0.9981 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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