Sabrina Bottazzi
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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: 3-classifier-finetuned-padchest
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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: 0.7250755287009063
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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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# 3-classifier-finetuned-padchest
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This model is a fine-tuned version of [nickmuchi/vit-finetuned-chest-xray-pneumonia](https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8505
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- Accuracy: 0.7251
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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: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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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| 2.0499 | 1.0 | 16 | 1.8761 | 0.3686 |
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| 1.704 | 2.0 | 32 | 1.5961 | 0.4955 |
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| 1.5393 | 3.0 | 48 | 1.3570 | 0.5770 |
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| 1.3161 | 4.0 | 64 | 1.2687 | 0.5770 |
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| 1.1991 | 5.0 | 80 | 1.1740 | 0.6073 |
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| 1.1459 | 6.0 | 96 | 1.1388 | 0.6073 |
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| 1.071 | 7.0 | 112 | 1.0763 | 0.6405 |
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| 0.9948 | 8.0 | 128 | 1.0419 | 0.6526 |
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| 0.9902 | 9.0 | 144 | 0.9869 | 0.6979 |
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| 0.9515 | 10.0 | 160 | 0.9825 | 0.6767 |
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| 0.9277 | 11.0 | 176 | 0.9645 | 0.6858 |
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| 0.9182 | 12.0 | 192 | 0.9264 | 0.7009 |
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| 0.895 | 13.0 | 208 | 0.9138 | 0.6979 |
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| 0.8765 | 14.0 | 224 | 0.9089 | 0.7100 |
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| 0.8536 | 15.0 | 240 | 0.8941 | 0.7009 |
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| 0.8385 | 16.0 | 256 | 0.8764 | 0.7221 |
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| 0.8187 | 17.0 | 272 | 0.8659 | 0.7160 |
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| 0.8172 | 18.0 | 288 | 0.8673 | 0.7069 |
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| 0.8101 | 19.0 | 304 | 0.8530 | 0.7341 |
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| 0.8127 | 20.0 | 320 | 0.8505 | 0.7251 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.18.0
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- Tokenizers 0.13.3
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