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README.md
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---
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license: apache-2.0
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base_model: microsoft/beit-large-patch16-384
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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: beit-large-patch16-384-limb-person-crop-8_5e-5_1e-3_0.15
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results: []
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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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# beit-large-patch16-384-limb-person-crop-8_5e-5_1e-3_0.15
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This model is a fine-tuned version of [microsoft/beit-large-patch16-384](https://huggingface.co/microsoft/beit-large-patch16-384) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3535
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- Accuracy: 0.3483
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 32
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- eval_batch_size: 32
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- seed: 2014
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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_steps: 500
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- num_epochs: 10.0
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- mixed_precision_training: Native AMP
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- label_smoothing_factor: 0.15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.3404 | 1.0 | 214 | 1.4186 | 0.3980 |
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| 1.3839 | 2.0 | 428 | 1.3841 | 0.2703 |
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| 1.3931 | 3.0 | 642 | 1.3867 | 0.2745 |
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| 1.3889 | 4.0 | 856 | 1.3884 | 0.2745 |
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| 1.3864 | 5.0 | 1070 | 1.3842 | 0.2761 |
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| 1.3892 | 6.0 | 1284 | 1.3802 | 0.2877 |
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| 1.369 | 7.0 | 1498 | 1.3726 | 0.3143 |
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| 1.3545 | 8.0 | 1712 | 1.3627 | 0.3275 |
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| 1.3626 | 9.0 | 1926 | 1.3594 | 0.3391 |
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| 1.3464 | 10.0 | 2140 | 1.3535 | 0.3483 |
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### Framework versions
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- Transformers 4.41.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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