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README.md
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@@ -4,17 +4,19 @@ base_model: VMware/roberta-base-mrqa
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tags:
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- generated_from_trainer
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model-index:
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- name: roberta-vmw-mrqa
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/favcowboy/huggingface/runs/vqu0a6tx)
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# roberta-vmw-mrqa
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This model is a fine-tuned version of [VMware/roberta-base-mrqa](https://huggingface.co/VMware/roberta-base-mrqa) on
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## Model description
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- Transformers 4.42.0.dev0
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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tags:
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- generated_from_trainer
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model-index:
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- name: roberta-vmw-mrqa
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results: []
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datasets:
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- enriquesaou/mrqa-squadded-sample
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/favcowboy/huggingface/runs/vqu0a6tx)
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# roberta-vmw-mrqa
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This model is a fine-tuned version of [VMware/roberta-base-mrqa](https://huggingface.co/VMware/roberta-base-mrqa) on a MRQA sample.
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## Model description
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- Transformers 4.42.0.dev0
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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