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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_11_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_11_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: 1.8389
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- F1: 0.8057
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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 | 0.4534 | 0.8011 |
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| 0.4027 | 2.0 | 576 | 0.4299 | 0.8121 |
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| 0.4027 | 3.0 | 864 | 0.4840 | 0.8142 |
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| 0.1947 | 4.0 | 1152 | 0.7501 | 0.7992 |
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| 0.1947 | 5.0 | 1440 | 1.0307 | 0.7866 |
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| 0.0771 | 6.0 | 1728 | 1.1292 | 0.8034 |
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| 0.0253 | 7.0 | 2016 | 1.2620 | 0.8033 |
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| 0.0253 | 8.0 | 2304 | 1.4065 | 0.7954 |
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| 0.0137 | 9.0 | 2592 | 1.4922 | 0.7887 |
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| 0.0137 | 10.0 | 2880 | 1.4922 | 0.8050 |
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| 0.0046 | 11.0 | 3168 | 1.4883 | 0.8097 |
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| 0.0046 | 12.0 | 3456 | 1.5542 | 0.8133 |
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| 0.0066 | 13.0 | 3744 | 1.5180 | 0.8000 |
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| 0.0094 | 14.0 | 4032 | 1.6762 | 0.7919 |
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| 0.0094 | 15.0 | 4320 | 1.5808 | 0.8005 |
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| 0.0047 | 16.0 | 4608 | 1.7025 | 0.8012 |
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| 0.0047 | 17.0 | 4896 | 1.6494 | 0.7986 |
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| 0.0039 | 18.0 | 5184 | 1.7218 | 0.8010 |
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| 0.0039 | 19.0 | 5472 | 1.8293 | 0.7994 |
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| 0.0005 | 20.0 | 5760 | 1.8142 | 0.7980 |
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| 0.0033 | 21.0 | 6048 | 1.8350 | 0.8037 |
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| 0.0033 | 22.0 | 6336 | 1.8361 | 0.8042 |
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| 0.0023 | 23.0 | 6624 | 1.8715 | 0.7996 |
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| 0.0023 | 24.0 | 6912 | 1.8411 | 0.8057 |
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| 0.0019 | 25.0 | 7200 | 1.8389 | 0.8057 |
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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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