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End of training

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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: cc
 
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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: racism-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 [davidmasip/racism](https://huggingface.co/davidmasip/racism) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0150
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- - Accuracy: 0.8560
 
 
 
 
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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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- | 0.2659 | 1.0 | 153 | 0.3250 | 0.8429 |
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- | 0.1191 | 2.0 | 306 | 0.5344 | 0.8380 |
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- | 0.0074 | 3.0 | 459 | 0.8188 | 0.8396 |
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- | 0.0001 | 4.0 | 612 | 0.9264 | 0.8462 |
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- | 0.0001 | 5.0 | 765 | 0.9551 | 0.8462 |
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- | 0.0001 | 6.0 | 918 | 0.9771 | 0.8527 |
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- | 0.0001 | 7.0 | 1071 | 0.9937 | 0.8527 |
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- | 0.0001 | 8.0 | 1224 | 1.0054 | 0.8560 |
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- | 0.0 | 9.0 | 1377 | 1.0126 | 0.8560 |
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- | 0.0001 | 10.0 | 1530 | 1.0150 | 0.8560 |
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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: cc
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+ base_model: davidmasip/racism
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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: racism-finetuned-detests
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  results: []
 
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  This model is a fine-tuned version of [davidmasip/racism](https://huggingface.co/davidmasip/racism) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1626
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+ - Accuracy: 0.8331
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+ - F1-score: 0.7625
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+ - Precision: 0.7625
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+ - Recall: 0.7625
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+ - Auc: 0.7625
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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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+ | 0.2554 | 1.0 | 174 | 0.3618 | 0.8380 | 0.7340 | 0.7901 | 0.7073 | 0.7073 |
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+ | 0.0488 | 2.0 | 348 | 0.7445 | 0.8282 | 0.7549 | 0.7556 | 0.7543 | 0.7543 |
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+ | 0.0005 | 3.0 | 522 | 0.9204 | 0.8429 | 0.7681 | 0.7794 | 0.7587 | 0.7587 |
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+ | 0.0001 | 4.0 | 696 | 1.0194 | 0.8462 | 0.7741 | 0.7838 | 0.7659 | 0.7659 |
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+ | 0.0001 | 5.0 | 870 | 1.0721 | 0.8363 | 0.7648 | 0.7676 | 0.7621 | 0.7621 |
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+ | 0.0001 | 6.0 | 1044 | 1.1081 | 0.8331 | 0.7625 | 0.7625 | 0.7625 | 0.7625 |
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+ | 0.0 | 7.0 | 1218 | 1.1324 | 0.8331 | 0.7625 | 0.7625 | 0.7625 | 0.7625 |
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+ | 0.0 | 8.0 | 1392 | 1.1492 | 0.8331 | 0.7625 | 0.7625 | 0.7625 | 0.7625 |
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+ | 0.0 | 9.0 | 1566 | 1.1592 | 0.8331 | 0.7625 | 0.7625 | 0.7625 | 0.7625 |
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+ | 0.0 | 10.0 | 1740 | 1.1626 | 0.8331 | 0.7625 | 0.7625 | 0.7625 | 0.7625 |
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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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