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leomaurodesenv
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roberta-base-answerable-or-not-augmented

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Model card Files
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End of training

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  1. README.md +14 -16
  2. model.safetensors +1 -1
README.md CHANGED
@@ -7,19 +7,19 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: roberta-base-answerable-or-not
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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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- # roberta-base-answerable-or-not
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0557
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- - Accuracy: 0.9949
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  ## Model description
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@@ -49,18 +49,16 @@ The following hyperparameters were used during training:
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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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- | 0.0819 | 1.0 | 198 | 0.1339 | 0.9797 |
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- | 0.0841 | 2.0 | 396 | 0.2775 | 0.9519 |
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- | 0.0439 | 3.0 | 594 | 0.1214 | 0.9797 |
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- | 0.0001 | 4.0 | 792 | 0.0805 | 0.9899 |
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- | 0.0001 | 5.0 | 990 | 0.0768 | 0.9924 |
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- | 0.0000 | 6.0 | 1188 | 0.1042 | 0.9873 |
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- | 0.0000 | 7.0 | 1386 | 0.0759 | 0.9924 |
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- | 0.0000 | 8.0 | 1584 | 0.0559 | 0.9949 |
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- | 0.0000 | 9.0 | 1782 | 0.0616 | 0.9924 |
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- | 0.0000 | 10.0 | 1980 | 0.0641 | 0.9924 |
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: roberta-base-answerable-or-not-augmented
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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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+ # roberta-base-answerable-or-not-augmented
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3072
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+ - Accuracy: 0.9396
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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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+ | 0.3439 | 1.0 | 1367 | 0.3772 | 0.8858 |
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+ | 0.2955 | 2.0 | 2734 | 0.3278 | 0.9199 |
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+ | 0.2421 | 3.0 | 4101 | 0.3375 | 0.9272 |
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+ | 0.1169 | 4.0 | 5468 | 0.3935 | 0.9265 |
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+ | 0.0190 | 5.0 | 6835 | 0.3073 | 0.9393 |
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+ | 0.2265 | 6.0 | 8202 | 0.4381 | 0.9283 |
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+ | 0.0310 | 7.0 | 9569 | 0.3289 | 0.9352 |
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+ | 0.0001 | 8.0 | 10936 | 0.4086 | 0.9371 |
 
 
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  ### Framework versions
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