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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: vit_tickers_binaryclf |
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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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# vit_tickers_binaryclf |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cord dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0116 |
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- F1: 0.9991 |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.0026 | 0.28 | 500 | 0.0187 | 0.9982 | |
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| 0.0186 | 0.56 | 1000 | 0.0116 | 0.9991 | |
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| 0.0006 | 0.84 | 1500 | 0.0044 | 0.9997 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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