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bert-base-uncased-finetuned-detests

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  1. README.md +25 -18
  2. pytorch_model.bin +1 -1
README.md CHANGED
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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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  - accuracy
 
 
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  model-index:
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  - name: bert-base-uncased-finetuned-detests
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  results: []
@@ -16,8 +19,12 @@ should probably proofread and complete it, then remove this comment. -->
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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: 1.0660
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- - Accuracy: 0.8232
 
 
 
 
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.4677 | 1.0 | 153 | 0.4412 | 0.8101 |
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- | 0.468 | 2.0 | 306 | 0.4210 | 0.8167 |
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- | 0.2216 | 3.0 | 459 | 0.4649 | 0.8183 |
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- | 0.1552 | 4.0 | 612 | 0.5008 | 0.8069 |
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- | 0.0962 | 5.0 | 765 | 0.7498 | 0.8347 |
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- | 0.0379 | 6.0 | 918 | 0.8682 | 0.8282 |
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- | 0.0026 | 7.0 | 1071 | 0.9450 | 0.8249 |
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- | 0.0202 | 8.0 | 1224 | 1.0202 | 0.8282 |
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- | 0.0011 | 9.0 | 1377 | 1.0601 | 0.8282 |
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- | 0.0305 | 10.0 | 1530 | 1.0660 | 0.8232 |
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  ### Framework versions
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- - Transformers 4.23.1
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- - Pytorch 1.12.1+cu113
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- - Datasets 2.6.1
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- - Tokenizers 0.13.1
 
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  ---
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  license: apache-2.0
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+ base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - precision
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+ - recall
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  model-index:
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  - name: bert-base-uncased-finetuned-detests
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  results: []
 
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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: 1.5026
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+ - Accuracy: 0.7856
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+ - F1-score: 0.7175
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+ - Precision: 0.7058
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+ - Recall: 0.7369
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+ - Auc: 0.7369
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
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+ | 0.271 | 1.0 | 174 | 0.4648 | 0.7954 | 0.7005 | 0.7070 | 0.6950 | 0.6950 |
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+ | 0.2246 | 2.0 | 348 | 0.5229 | 0.7987 | 0.7053 | 0.7119 | 0.6997 | 0.6997 |
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+ | 0.3814 | 3.0 | 522 | 0.7043 | 0.7676 | 0.7018 | 0.6896 | 0.7278 | 0.7278 |
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+ | 0.1343 | 4.0 | 696 | 0.8843 | 0.7938 | 0.7217 | 0.7124 | 0.7346 | 0.7346 |
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+ | 0.0063 | 5.0 | 870 | 1.0890 | 0.7807 | 0.7040 | 0.6955 | 0.7159 | 0.7159 |
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+ | 0.063 | 6.0 | 1044 | 1.1208 | 0.8101 | 0.7378 | 0.7316 | 0.7452 | 0.7452 |
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+ | 0.0022 | 7.0 | 1218 | 1.1989 | 0.8249 | 0.7318 | 0.7543 | 0.7166 | 0.7166 |
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+ | 0.0356 | 8.0 | 1392 | 1.5295 | 0.7758 | 0.7151 | 0.7016 | 0.7457 | 0.7457 |
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+ | 0.0002 | 9.0 | 1566 | 1.4269 | 0.8003 | 0.7202 | 0.7171 | 0.7236 | 0.7236 |
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+ | 0.0004 | 10.0 | 1740 | 1.5026 | 0.7856 | 0.7175 | 0.7058 | 0.7369 | 0.7369 |
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  ### Framework versions
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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