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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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- 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-5_5e-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-5_5e-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: 0.8764 |
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- Accuracy: 0.7181 |
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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: 1e-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: 0.1 |
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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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| 1.4023 | 1.0 | 214 | 1.3975 | 0.2745 | |
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| 1.2554 | 2.0 | 428 | 1.1980 | 0.4900 | |
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| 1.1635 | 3.0 | 642 | 1.0272 | 0.5970 | |
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| 1.099 | 4.0 | 856 | 1.0476 | 0.5954 | |
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| 1.067 | 5.0 | 1070 | 0.9586 | 0.6600 | |
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| 1.0153 | 6.0 | 1284 | 0.9101 | 0.6816 | |
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| 0.9507 | 7.0 | 1498 | 0.9307 | 0.6833 | |
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| 0.9487 | 8.0 | 1712 | 0.8812 | 0.7148 | |
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| 0.9365 | 9.0 | 1926 | 0.8764 | 0.7181 | |
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| 0.9186 | 10.0 | 2140 | 0.8818 | 0.7090 | |
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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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