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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_RMSprop_1e5_20Epoch_Beit-large-224_fold5
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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: 0.8631752125034274
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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_RMSprop_1e5_20Epoch_Beit-large-224_fold5
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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: 1.6377
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+ - Accuracy: 0.8632
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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: 1e-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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+ - 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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+ | 0.4668 | 1.0 | 914 | 0.3852 | 0.8385 |
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+ | 0.2261 | 2.0 | 1828 | 0.3623 | 0.8645 |
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+ | 0.1143 | 3.0 | 2742 | 0.5165 | 0.8580 |
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+ | 0.2149 | 4.0 | 3656 | 0.7493 | 0.8626 |
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+ | 0.1035 | 5.0 | 4570 | 1.0893 | 0.8607 |
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+ | 0.0224 | 6.0 | 5484 | 1.3211 | 0.8582 |
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+ | 0.0055 | 7.0 | 6398 | 1.5211 | 0.8604 |
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+ | 0.0001 | 8.0 | 7312 | 1.6383 | 0.8563 |
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+ | 0.0001 | 9.0 | 8226 | 1.6304 | 0.8678 |
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+ | 0.0 | 10.0 | 9140 | 1.6377 | 0.8632 |
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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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