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ccaf1be
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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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- cifar10
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metrics:
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- accuracy
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model-index:
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- name: cifarv2
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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: cifar10
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type: cifar10
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config: plain_text
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split: train[:20000]
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args: plain_text
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.921
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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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# cifarv2
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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 cifar10 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2653
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- Accuracy: 0.921
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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: 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: 10
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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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| 0.6994 | 1.0 | 250 | 0.7132 | 0.8758 |
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| 0.4271 | 2.0 | 500 | 0.4477 | 0.894 |
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| 0.3112 | 3.0 | 750 | 0.3905 | 0.8942 |
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| 0.3139 | 4.0 | 1000 | 0.3207 | 0.9115 |
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| 0.2511 | 5.0 | 1250 | 0.3288 | 0.9048 |
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| 0.2652 | 6.0 | 1500 | 0.2977 | 0.9125 |
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| 0.2392 | 7.0 | 1750 | 0.2720 | 0.9187 |
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| 0.1759 | 8.0 | 2000 | 0.2670 | 0.9173 |
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| 0.2024 | 9.0 | 2250 | 0.2606 | 0.9193 |
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| 0.1774 | 10.0 | 2500 | 0.2653 | 0.921 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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