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End of training

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  1. README.md +72 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: my_awesome_mingliangqiangu_model
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+ results: []
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+ ---
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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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+
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+ # my_awesome_mingliangqiangu_model
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+
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1140
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+ - Accuracy: 0.9981
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.7575 | 0.99 | 67 | 1.3989 | 0.9287 |
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+ | 0.4806 | 2.0 | 135 | 0.4502 | 0.9935 |
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+ | 0.2902 | 2.99 | 202 | 0.2922 | 0.9944 |
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+ | 0.2073 | 4.0 | 270 | 0.2118 | 0.9981 |
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+ | 0.1975 | 4.99 | 337 | 0.1831 | 0.9963 |
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+ | 0.1514 | 6.0 | 405 | 0.1576 | 0.9935 |
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+ | 0.1282 | 6.99 | 472 | 0.1290 | 1.0 |
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+ | 0.1224 | 8.0 | 540 | 0.1317 | 0.9963 |
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+ | 0.1147 | 8.99 | 607 | 0.1127 | 1.0 |
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+ | 0.1129 | 9.93 | 670 | 0.1140 | 0.9981 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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