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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: Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold2
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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: 0.8397297297297297
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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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+ # Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold2
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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: 1.6549
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+ - Accuracy: 0.8397
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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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+ | 0.4334 | 1.0 | 923 | 0.4261 | 0.8314 |
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+ | 0.3478 | 2.0 | 1846 | 0.4091 | 0.8357 |
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+ | 0.2025 | 3.0 | 2769 | 0.6347 | 0.8408 |
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+ | 0.0819 | 4.0 | 3692 | 0.8142 | 0.8341 |
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+ | 0.1361 | 5.0 | 4615 | 1.0819 | 0.8441 |
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+ | 0.0324 | 6.0 | 5538 | 1.3598 | 0.8427 |
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+ | 0.0035 | 7.0 | 6461 | 1.6238 | 0.8430 |
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+ | 0.0 | 8.0 | 7384 | 1.6312 | 0.8405 |
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+ | 0.0002 | 9.0 | 8307 | 1.6680 | 0.8405 |
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+ | 0.0001 | 10.0 | 9230 | 1.6549 | 0.8397 |
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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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