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---
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license: apache-2.0
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base_model: microsoft/resnet-152
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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: Dogs-Breed-Image-Classification-V2
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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: 0.8408163265306122
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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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# Dogs-Breed-Image-Classification-V2
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This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0115
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- Accuracy: 0.8408
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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-06
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- train_batch_size: 32
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- eval_batch_size: 32
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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: linear
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- num_epochs: 20
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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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| No log | 1.0 | 483 | 4.6525 | 0.7382 |
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| 4.7329 | 2.0 | 966 | 4.3558 | 0.7298 |
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| 4.5033 | 3.0 | 1449 | 3.9568 | 0.7471 |
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| 4.1405 | 4.0 | 1932 | 3.5160 | 0.7782 |
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| 3.7176 | 5.0 | 2415 | 3.0805 | 0.7946 |
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| 3.293 | 6.0 | 2898 | 2.6907 | 0.8021 |
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| 2.8898 | 7.0 | 3381 | 2.3044 | 0.8126 |
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| 2.5343 | 8.0 | 3864 | 2.0091 | 0.8177 |
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| 2.2188 | 9.0 | 4347 | 1.7910 | 0.8126 |
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| 1.9698 | 10.0 | 4830 | 1.6015 | 0.8194 |
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| 1.7532 | 11.0 | 5313 | 1.4383 | 0.8220 |
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| 1.586 | 12.0 | 5796 | 1.3355 | 0.8264 |
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| 1.4533 | 13.0 | 6279 | 1.2467 | 0.8260 |
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| 1.336 | 14.0 | 6762 | 1.1575 | 0.8313 |
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| 1.2641 | 15.0 | 7245 | 1.1038 | 0.8321 |
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| 1.185 | 16.0 | 7728 | 1.0606 | 0.8395 |
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| 1.1329 | 17.0 | 8211 | 1.0178 | 0.8398 |
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| 1.0977 | 18.0 | 8694 | 1.0115 | 0.8408 |
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| 1.0732 | 19.0 | 9177 | 0.9945 | 0.8381 |
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| 1.0508 | 20.0 | 9660 | 0.9930 | 0.8393 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.3.0
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- Datasets 2.15.0
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- Tokenizers 0.15.1
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