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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-152-finetuned_resnet152-adam-optimizere-2-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: 0.8980952380952381
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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-152-finetuned_resnet152-adam-optimizere-2-autotags
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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: 0.4368
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- Accuracy: 0.8981
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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: 0.01
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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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| 1.4424 | 0.99 | 65 | 1.7123 | 0.56 |
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| 1.6053 | 1.99 | 130 | 2.0613 | 0.3152 |
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| 1.3795 | 2.99 | 195 | 1.3791 | 0.5552 |
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| 0.9701 | 3.99 | 260 | 0.9195 | 0.7038 |
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| 0.8258 | 4.99 | 325 | 0.9107 | 0.7067 |
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| 0.7619 | 5.99 | 390 | 0.9915 | 0.6867 |
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| 0.6241 | 6.99 | 455 | 0.7895 | 0.76 |
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| 0.497 | 7.99 | 520 | 0.6616 | 0.8038 |
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| 0.4709 | 8.99 | 585 | 0.5282 | 0.8543 |
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| 0.394 | 9.99 | 650 | 0.5447 | 0.8429 |
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| 0.343 | 10.99 | 715 | 0.5108 | 0.8486 |
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| 0.3482 | 11.99 | 780 | 0.5224 | 0.8505 |
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| 0.2576 | 12.99 | 845 | 0.4796 | 0.8743 |
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| 0.1837 | 13.99 | 910 | 0.5008 | 0.8571 |
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| 0.1904 | 14.99 | 975 | 0.4366 | 0.8790 |
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| 0.1458 | 15.99 | 1040 | 0.4320 | 0.8990 |
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| 0.1575 | 16.99 | 1105 | 0.4059 | 0.8952 |
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| 0.0992 | 17.99 | 1170 | 0.4362 | 0.8952 |
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| 0.0858 | 18.99 | 1235 | 0.4210 | 0.8971 |
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| 0.0704 | 19.99 | 1300 | 0.4368 | 0.8981 |
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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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