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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: levit-192_finetuned_on_unlabelled_IA_with_snorkel_labels
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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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# levit-192_finetuned_on_unlabelled_IA_with_snorkel_labels
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This model is a fine-tuned version of [facebook/levit-192](https://huggingface.co/facebook/levit-192) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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- Precision: 0.9836
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- Recall: 0.9822
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- F1: 0.9829
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- Accuracy: 0.9873
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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: 128
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- eval_batch_size: 256
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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: 10
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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 | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 253 | nan | 0.9743 | 0.9791 | 0.9766 | 0.9826 |
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| 0.0557 | 2.0 | 506 | nan | 0.9829 | 0.9801 | 0.9815 | 0.9863 |
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| 0.0557 | 3.0 | 759 | nan | 0.9836 | 0.9822 | 0.9829 | 0.9873 |
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| 0.0543 | 4.0 | 1012 | nan | 0.9839 | 0.9775 | 0.9807 | 0.9858 |
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| 0.0543 | 5.0 | 1265 | nan | 0.9616 | 0.9727 | 0.9670 | 0.9752 |
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| 0.0457 | 6.0 | 1518 | nan | 0.9563 | 0.9699 | 0.9629 | 0.9720 |
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| 0.0457 | 7.0 | 1771 | nan | 0.9822 | 0.9808 | 0.9815 | 0.9863 |
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| 0.0418 | 8.0 | 2024 | nan | 0.9735 | 0.9769 | 0.9752 | 0.9815 |
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| 0.0418 | 9.0 | 2277 | nan | 0.9832 | 0.9811 | 0.9822 | 0.9868 |
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| 0.0396 | 10.0 | 2530 | nan | 0.9843 | 0.9815 | 0.9829 | 0.9873 |
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### Framework versions
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- Transformers 4.22.2
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- Pytorch 1.12.1+cu113
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- Datasets 2.5.2
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- Tokenizers 0.12.1
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