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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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- recall
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model-index:
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- name: vca
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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: test
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args: default
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metrics:
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- name: Recall
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type: recall
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value: 0.7818181818181819
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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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# vca
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3844
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- Recall: 0.7818
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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: cosine_with_restarts
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 30
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 1.0 | 11 | 0.4763 | 0.6987 |
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| No log | 2.0 | 22 | 0.4438 | 0.6390 |
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| No log | 3.0 | 33 | 0.4511 | 0.5870 |
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| No log | 4.0 | 44 | 0.4084 | 0.7610 |
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| No log | 5.0 | 55 | 0.3562 | 0.8078 |
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| No log | 6.0 | 66 | 0.3844 | 0.7818 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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