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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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- # bert-base-uncased-finetuned-squad2
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the squad_v2 dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.3537
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  BERTbase fine-tuned on SQuAD 2.0 : Encoder-based Transformer Language model, pretrained with Masked Language Modeling and Next Sentence Prediction.<br>
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  Suitable for Question-Answering tasks, predicts answer spans within the context provided.<br>
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- Training data: Train-set SQuAD2.0<br>
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- Evaluation data: Validation-set SQuAD2.0<br>
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- Hardware Accelerator used: GPU Tesla T4
 
 
 
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  ## Intended uses & limitations
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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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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the squad_v2 dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.3537
 
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  BERTbase fine-tuned on SQuAD 2.0 : Encoder-based Transformer Language model, pretrained with Masked Language Modeling and Next Sentence Prediction.<br>
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  Suitable for Question-Answering tasks, predicts answer spans within the context provided.<br>
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+ **Language model:** bert-base-uncased
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+ **Language:** English
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+ **Downstream-task:** Question-Answering
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+ **Training data:** Train-set SQuAD 2.0
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+ **Evaluation data:** Evaluation-set SQuAD 2.0
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+ **Hardware Accelerator used**: GPU Tesla T4
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  ## Intended uses & limitations
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