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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_7_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_7_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: 1.7559
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- F1: 0.8004
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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 | 288 | 0.4132 | 0.7956 |
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| 0.405 | 2.0 | 576 | 0.4076 | 0.8100 |
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| 0.405 | 3.0 | 864 | 0.5147 | 0.8160 |
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| 0.1887 | 4.0 | 1152 | 0.8412 | 0.7926 |
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| 0.1887 | 5.0 | 1440 | 0.9743 | 0.7910 |
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| 0.0886 | 6.0 | 1728 | 0.9539 | 0.8010 |
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| 0.0389 | 7.0 | 2016 | 1.0582 | 0.8042 |
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| 0.0389 | 8.0 | 2304 | 1.2592 | 0.7911 |
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| 0.0224 | 9.0 | 2592 | 1.3355 | 0.7987 |
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| 0.0224 | 10.0 | 2880 | 1.3268 | 0.8051 |
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| 0.014 | 11.0 | 3168 | 1.5071 | 0.7970 |
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| 0.014 | 12.0 | 3456 | 1.5979 | 0.7935 |
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| 0.0057 | 13.0 | 3744 | 1.4898 | 0.8052 |
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| 0.0136 | 14.0 | 4032 | 1.4505 | 0.8133 |
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| 0.0136 | 15.0 | 4320 | 1.6039 | 0.7930 |
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| 0.0043 | 16.0 | 4608 | 1.5160 | 0.8075 |
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| 0.0043 | 17.0 | 4896 | 1.5439 | 0.8074 |
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| 0.0036 | 18.0 | 5184 | 1.5788 | 0.8131 |
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| 0.0036 | 19.0 | 5472 | 1.6153 | 0.8085 |
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| 0.0007 | 20.0 | 5760 | 1.6258 | 0.8113 |
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| 0.0021 | 21.0 | 6048 | 1.7087 | 0.8023 |
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| 0.0021 | 22.0 | 6336 | 1.7146 | 0.8032 |
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| 0.0016 | 23.0 | 6624 | 1.7504 | 0.8018 |
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| 0.0016 | 24.0 | 6912 | 1.7685 | 0.8023 |
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| 0.0001 | 25.0 | 7200 | 1.7559 | 0.8004 |
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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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