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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-large-patch16-224
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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: Boya2_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold1
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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: Accuracy
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+ type: accuracy
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+ value: 0.8595336076817558
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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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+ # Boya2_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold1
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+
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+ This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4832
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+ - Accuracy: 0.8595
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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: 0.0001
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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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+ - 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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+ | 0.3205 | 1.0 | 914 | 0.4126 | 0.8335 |
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+ | 0.3896 | 2.0 | 1828 | 0.3489 | 0.8595 |
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+ | 0.2815 | 3.0 | 2742 | 0.4941 | 0.8250 |
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+ | 0.0932 | 4.0 | 3656 | 0.8851 | 0.8431 |
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+ | 0.0061 | 5.0 | 4570 | 1.0518 | 0.8527 |
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+ | 0.0199 | 6.0 | 5484 | 1.2561 | 0.8529 |
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+ | 0.0725 | 7.0 | 6398 | 1.4266 | 0.8565 |
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+ | 0.0 | 8.0 | 7312 | 1.4824 | 0.8543 |
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+ | 0.0 | 9.0 | 8226 | 1.4678 | 0.8579 |
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+ | 0.0 | 10.0 | 9140 | 1.4832 | 0.8595 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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