02shanky / test_model_graphics_classification

huggingface.co
Total runs: 9
24-hour runs: 0
7-day runs: 0
30-day runs: 2
Model's Last Updated: July 07 2023
image-classification

Introduction of test_model_graphics_classification

Model Details of test_model_graphics_classification

test_model_graphics_classification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1381
  • Accuracy: 0.9842
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.1521 0.98 44 0.1381 0.9842
Framework versions
  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3

Runs of 02shanky test_model_graphics_classification on huggingface.co

9
Total runs
0
24-hour runs
-2
3-day runs
0
7-day runs
2
30-day runs

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test_model_graphics_classification huggingface.co is an AI model on huggingface.co that provides test_model_graphics_classification's model effect (), which can be used instantly with this 02shanky test_model_graphics_classification model. huggingface.co supports a free trial of the test_model_graphics_classification model, and also provides paid use of the test_model_graphics_classification. Support call test_model_graphics_classification model through api, including Node.js, Python, http.

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https://huggingface.co/02shanky/test_model_graphics_classification

test_model_graphics_classification install

test_model_graphics_classification is an open source model from GitHub that offers a free installation service, and any user can find test_model_graphics_classification on GitHub to install. At the same time, huggingface.co provides the effect of test_model_graphics_classification install, users can directly use test_model_graphics_classification installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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