lora info
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README.md
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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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#
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on [SWAG](https://huggingface.co/datasets/allenai/swag) dataset.
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It achieves the following results on the evaluation set:
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## Model description
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More information needed
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## Intended uses & limitations
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- name: bert-base-uncased-swag
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results: []
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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-swag
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on [SWAG](https://huggingface.co/datasets/allenai/swag) dataset.
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It achieves the following results on the evaluation set:
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## Model description
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## Intended uses & limitations
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## Training procedure
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Our approach focuses explicitly on adapting the Transformers weights' Wq (query) and Wv (value) in the attention module for parameter efficiency.
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### Training hyperparameters
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The following hyperparameters were used during training:
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