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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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- f1 |
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model-index: |
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- name: convnextv2-base-22k-384 |
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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: F1 |
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type: f1 |
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value: 0.9913113141099743 |
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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-384 |
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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: 0.0069 |
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- F1: 0.9913 |
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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: 4 |
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- total_train_batch_size: 32 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.1521 | 1.0 | 202 | 0.0982 | 0.8278 | |
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| 0.0664 | 2.0 | 404 | 0.0626 | 0.9079 | |
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| 0.1053 | 3.0 | 606 | 0.0356 | 0.9537 | |
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| 0.0432 | 4.0 | 808 | 0.0302 | 0.9703 | |
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| 0.0552 | 5.0 | 1010 | 0.0114 | 0.9827 | |
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| 0.0352 | 6.0 | 1212 | 0.0131 | 0.9824 | |
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| 0.0221 | 7.0 | 1414 | 0.0063 | 0.9943 | |
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| 0.0018 | 8.0 | 1616 | 0.0169 | 0.9824 | |
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| 0.0283 | 9.0 | 1818 | 0.0028 | 0.9971 | |
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| 0.0429 | 10.0 | 2020 | 0.0069 | 0.9913 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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