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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-15ep |
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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: 0.9431411530815109 |
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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-15ep |
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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: 0.3192 |
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- Accuracy: 0.9431 |
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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: 0.0001 |
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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: 15 |
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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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| 0.5717 | 1.0 | 1099 | 0.4616 | 0.8573 | |
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| 0.4653 | 2.0 | 2198 | 0.3607 | 0.8970 | |
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| 0.3449 | 3.0 | 3297 | 0.4104 | 0.8950 | |
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| 0.3522 | 4.0 | 4396 | 0.3755 | 0.9026 | |
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| 0.28 | 5.0 | 5495 | 0.3756 | 0.9066 | |
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| 0.2456 | 6.0 | 6594 | 0.3496 | 0.9173 | |
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| 0.2141 | 7.0 | 7693 | 0.3612 | 0.9201 | |
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| 0.1458 | 8.0 | 8792 | 0.3391 | 0.9304 | |
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| 0.1842 | 9.0 | 9891 | 0.3353 | 0.9328 | |
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| 0.1037 | 10.0 | 10990 | 0.3383 | 0.9356 | |
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| 0.0747 | 11.0 | 12089 | 0.3345 | 0.9368 | |
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| 0.0912 | 12.0 | 13188 | 0.3244 | 0.9392 | |
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| 0.0733 | 13.0 | 14287 | 0.3219 | 0.9408 | |
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| 0.0667 | 14.0 | 15386 | 0.3190 | 0.9435 | |
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| 0.0694 | 15.0 | 16485 | 0.3192 | 0.9431 | |
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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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