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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-50-finetuned-brain-tumor
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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: 0.9171249018067557
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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-50-finetuned-brain-tumor
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2757
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- Accuracy: 0.9171
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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-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 256
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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: 15
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### Training results
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| Training Loss | Epoch | Step | Accuracy | Validation Loss |
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|:-------------:|:-----:|:----:|:--------:|:---------------:|
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| 1.3264 | 1.0 | 30 | 0.5035 | 1.3154 |
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| 1.222 | 2.0 | 60 | 0.6473 | 1.2254 |
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| 1.0584 | 3.0 | 90 | 1.0668 | 0.7510 |
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| 0.8977 | 4.0 | 120 | 0.9205 | 0.8060 |
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| 0.724 | 5.0 | 150 | 0.7740 | 0.8456 |
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| 0.6025 | 6.0 | 180 | 0.6009 | 0.8720 |
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| 0.4953 | 7.0 | 210 | 0.5039 | 0.8684 |
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| 0.4252 | 8.0 | 240 | 0.4158 | 0.8904 |
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| 0.3677 | 9.0 | 270 | 0.3705 | 0.9038 |
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| 0.3305 | 10.0 | 300 | 0.3300 | 0.9049 |
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| 0.3113 | 11.0 | 330 | 0.3053 | 0.9097 |
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| 0.2835 | 12.0 | 360 | 0.2885 | 0.9116 |
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| 0.2614 | 13.0 | 390 | 0.2606 | 0.9297 |
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| 0.2735 | 14.0 | 420 | 0.2767 | 0.9187 |
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| 0.2573 | 15.0 | 450 | 0.2757 | 0.9171 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.10.0
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- Tokenizers 0.13.2
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