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arincon
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roberta-base-autextification

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
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arincon commited on
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End of training

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Files changed (3) hide show
  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.43
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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
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the au_tex_tification dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7197
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- - Accuracy: 0.43
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- - Roc Auc: 0.5753
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|
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- | 0.7023 | 1.0 | 10 | 0.6594 | 0.65 | 0.6923 |
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- | 0.7188 | 2.0 | 20 | 0.6659 | 0.65 | 0.7692 |
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- | 0.6933 | 3.0 | 30 | 0.6722 | 0.65 | 0.7692 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.487449615243679
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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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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the au_tex_tification dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6933
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+ - Accuracy: 0.4874
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+ - Roc Auc: 0.6293
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|
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+ | 0.6902 | 1.0 | 3385 | 0.7003 | 0.4924 | 0.6494 |
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+ | 0.6873 | 2.0 | 6770 | 0.6935 | 0.5076 | 0.7272 |
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+ | 0.6949 | 3.0 | 10155 | 0.6931 | 0.5076 | 0.7407 |
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  ### Framework versions
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