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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-optimizer5e-4-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: 0.9304761904761905
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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-optimizer5e-4-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: 0.2399
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- Accuracy: 0.9305
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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: 0.0005
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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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| 2.4009 | 0.99 | 65 | 2.1414 | 0.3971 |
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| 0.9201 | 1.99 | 130 | 0.8123 | 0.7210 |
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| 0.7575 | 2.99 | 195 | 0.5730 | 0.8124 |
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| 0.4792 | 3.99 | 260 | 0.4166 | 0.8648 |
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| 0.4253 | 4.99 | 325 | 0.3811 | 0.8810 |
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| 0.3331 | 5.99 | 390 | 0.4290 | 0.8705 |
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| 0.2347 | 6.99 | 455 | 0.4600 | 0.8952 |
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| 0.1732 | 7.99 | 520 | 0.3018 | 0.8924 |
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| 0.1777 | 8.99 | 585 | 0.4851 | 0.8914 |
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| 0.1298 | 9.99 | 650 | 0.2941 | 0.92 |
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| 0.1164 | 10.99 | 715 | 0.3915 | 0.9095 |
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| 0.1284 | 11.99 | 780 | 0.3701 | 0.9152 |
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| 0.0986 | 12.99 | 845 | 0.3416 | 0.9171 |
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| 0.0944 | 13.99 | 910 | 0.3145 | 0.9210 |
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| 0.0929 | 14.99 | 975 | 0.2677 | 0.9229 |
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| 0.1014 | 15.99 | 1040 | 0.2745 | 0.9295 |
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| 0.0971 | 16.99 | 1105 | 0.2932 | 0.9267 |
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| 0.0691 | 17.99 | 1170 | 0.2174 | 0.9333 |
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| 0.0557 | 18.99 | 1235 | 0.2233 | 0.9324 |
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| 0.06 | 19.99 | 1300 | 0.2399 | 0.9305 |
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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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