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fine-tune-vanilla-bert-base-uncased-ch9

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update model card README.md

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@@ -5,8 +5,6 @@ tags:
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  model-index:
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  - name: fine-tune-vanilla-bert-base-uncased-ch9
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  results: []
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- datasets:
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- - Francesco-A/github-issues_huggingface-datasets
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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
@@ -14,11 +12,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # fine-tune-vanilla-bert-base-uncased-ch9
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- This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1877
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- - Micro f1: 0.7208
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- - Macro f1: 0.6293
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  ## Model description
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@@ -49,16 +47,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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- | 0.4535 | 1.0 | 56 | 0.3607 | 0.0 | 0.0 |
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- | 0.3388 | 2.0 | 112 | 0.3270 | 0.0 | 0.0 |
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- | 0.3023 | 3.0 | 168 | 0.2794 | 0.4654 | 0.2139 |
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- | 0.2515 | 4.0 | 224 | 0.2420 | 0.4750 | 0.1855 |
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- | 0.2095 | 5.0 | 280 | 0.2263 | 0.5318 | 0.2599 |
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- | 0.1673 | 6.0 | 336 | 0.2135 | 0.6429 | 0.4327 |
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- | 0.1424 | 7.0 | 392 | 0.1885 | 0.6631 | 0.4890 |
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- | 0.1049 | 8.0 | 448 | 0.1801 | 0.7164 | 0.6139 |
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- | 0.08 | 9.0 | 504 | 0.1802 | 0.7136 | 0.6020 |
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- | 0.0637 | 10.0 | 560 | 0.1877 | 0.7208 | 0.6293 |
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  ### Framework versions
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  - Transformers 4.16.2
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  - Pytorch 2.1.0+cu118
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  - Datasets 1.16.1
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- - Tokenizers 0.15.0
 
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  model-index:
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  - name: fine-tune-vanilla-bert-base-uncased-ch9
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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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  # fine-tune-vanilla-bert-base-uncased-ch9
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+ This model is a fine-tuned version of [omersubasi/bert-base-uncased-issues-128](https://huggingface.co/omersubasi/bert-base-uncased-issues-128) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1664
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+ - Micro f1: 0.7308
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+ - Macro f1: 0.6418
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 0.3943 | 1.0 | 56 | 0.3426 | 0.0 | 0.0 |
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+ | 0.3165 | 2.0 | 112 | 0.3111 | 0.2857 | 0.1010 |
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+ | 0.2701 | 3.0 | 168 | 0.2531 | 0.5 | 0.2266 |
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+ | 0.2019 | 4.0 | 224 | 0.2155 | 0.6196 | 0.3375 |
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+ | 0.1544 | 5.0 | 280 | 0.2094 | 0.6064 | 0.4363 |
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+ | 0.1135 | 6.0 | 336 | 0.1829 | 0.7030 | 0.5914 |
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+ | 0.0823 | 7.0 | 392 | 0.1774 | 0.6970 | 0.5956 |
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+ | 0.0619 | 8.0 | 448 | 0.1781 | 0.6965 | 0.6130 |
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+ | 0.0491 | 9.0 | 504 | 0.1695 | 0.7327 | 0.6402 |
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+ | 0.0419 | 10.0 | 560 | 0.1664 | 0.7308 | 0.6418 |
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  ### Framework versions
 
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  - Transformers 4.16.2
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  - Pytorch 2.1.0+cu118
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  - Datasets 1.16.1
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+ - Tokenizers 0.15.0