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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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- image-classification |
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- vision |
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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_1e-4_1e-3_0.1 |
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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_1e-4_1e-3_0.1 |
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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 the c14kevincardenas/beta_caller_284_person_crop dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8104 |
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- Accuracy: 0.7629 |
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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: 0.0001 |
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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: 0.1 |
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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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| 1.2934 | 1.0 | 214 | 1.3109 | 0.4585 | |
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| 1.1806 | 2.0 | 428 | 1.1092 | 0.5564 | |
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| 1.181 | 3.0 | 642 | 1.0387 | 0.6078 | |
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| 1.1188 | 4.0 | 856 | 0.9513 | 0.6667 | |
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| 1.0883 | 5.0 | 1070 | 0.9218 | 0.6849 | |
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| 1.0148 | 6.0 | 1284 | 0.8751 | 0.7106 | |
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| 0.9767 | 7.0 | 1498 | 0.8362 | 0.7463 | |
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| 0.9218 | 8.0 | 1712 | 0.8223 | 0.7463 | |
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| 0.8507 | 9.0 | 1926 | 0.8148 | 0.7620 | |
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| 0.8348 | 10.0 | 2140 | 0.8104 | 0.7629 | |
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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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