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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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- f1
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model-index:
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- name: distilbert-base-uncased_fold_2_binary_v1
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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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# distilbert-base-uncased_fold_2_binary_v1
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8833
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- F1: 0.7841
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 25
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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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| No log | 1.0 | 290 | 0.4060 | 0.8070 |
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| 0.3981 | 2.0 | 580 | 0.4534 | 0.8072 |
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| 0.3981 | 3.0 | 870 | 0.5460 | 0.7961 |
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| 0.1985 | 4.0 | 1160 | 0.8684 | 0.7818 |
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| 0.1985 | 5.0 | 1450 | 0.9009 | 0.7873 |
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| 0.0844 | 6.0 | 1740 | 1.1529 | 0.7825 |
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| 0.0329 | 7.0 | 2030 | 1.3185 | 0.7850 |
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| 0.0329 | 8.0 | 2320 | 1.4110 | 0.7862 |
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| 0.0109 | 9.0 | 2610 | 1.4751 | 0.7784 |
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| 0.0109 | 10.0 | 2900 | 1.6276 | 0.7723 |
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| 0.0071 | 11.0 | 3190 | 1.6779 | 0.7861 |
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| 0.0071 | 12.0 | 3480 | 1.6258 | 0.7850 |
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| 0.0041 | 13.0 | 3770 | 1.6324 | 0.7903 |
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| 0.0109 | 14.0 | 4060 | 1.7563 | 0.7932 |
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| 0.0109 | 15.0 | 4350 | 1.6740 | 0.7906 |
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| 0.0079 | 16.0 | 4640 | 1.7468 | 0.7944 |
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| 0.0079 | 17.0 | 4930 | 1.7095 | 0.7879 |
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| 0.0067 | 18.0 | 5220 | 1.7293 | 0.7912 |
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| 0.0021 | 19.0 | 5510 | 1.7875 | 0.7848 |
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| 0.0021 | 20.0 | 5800 | 1.7462 | 0.7906 |
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| 0.0026 | 21.0 | 6090 | 1.8549 | 0.7815 |
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| 0.0026 | 22.0 | 6380 | 1.8314 | 0.7860 |
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| 0.0021 | 23.0 | 6670 | 1.8577 | 0.7839 |
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| 0.0021 | 24.0 | 6960 | 1.8548 | 0.7883 |
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| 0.0001 | 25.0 | 7250 | 1.8833 | 0.7841 |
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### Framework versions
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- Transformers 4.21.0
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- Pytorch 1.12.0+cu113
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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