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update model card README.md
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README.md
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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: resnet-101-finetuned_resnet101-sgd-optimizer20-autotags
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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: 0.8847619047619047
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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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# resnet-101-finetuned_resnet101-sgd-optimizer20-autotags
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This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3318
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- Accuracy: 0.8848
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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: 0.1
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 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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| 1.1302 | 0.99 | 65 | 1.0040 | 0.6724 |
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| 1.1708 | 1.99 | 130 | 1.4856 | 0.5495 |
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| 1.141 | 2.99 | 195 | 1.1486 | 0.6352 |
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| 1.0119 | 3.99 | 260 | 0.8829 | 0.7314 |
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| 0.8091 | 4.99 | 325 | 0.8301 | 0.7419 |
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| 0.7878 | 5.99 | 390 | 0.8121 | 0.7333 |
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| 0.6827 | 6.99 | 455 | 0.6047 | 0.7990 |
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| 0.5525 | 7.99 | 520 | 0.6028 | 0.8048 |
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| 0.5787 | 8.99 | 585 | 0.5183 | 0.8352 |
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| 0.4797 | 9.99 | 650 | 0.4737 | 0.8543 |
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| 0.4224 | 10.99 | 715 | 0.4943 | 0.8305 |
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| 0.4389 | 11.99 | 780 | 0.4162 | 0.8629 |
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| 0.4142 | 12.99 | 845 | 0.4000 | 0.8629 |
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| 0.3144 | 13.99 | 910 | 0.3833 | 0.8695 |
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| 0.2915 | 14.99 | 975 | 0.3688 | 0.8733 |
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| 0.3302 | 15.99 | 1040 | 0.3643 | 0.8810 |
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| 0.2954 | 16.99 | 1105 | 0.3446 | 0.8867 |
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| 0.2186 | 17.99 | 1170 | 0.3571 | 0.8905 |
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| 0.1812 | 18.99 | 1235 | 0.3334 | 0.8886 |
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| 0.1911 | 19.99 | 1300 | 0.3318 | 0.8848 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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