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This learned metric is for evaluating models trained on the TaTA dataset. It was trained as per instructions in [TaTA: A Multilingual Table-to-Text Dataset for African Languages](https://aclanthology.org/2023.findings-emnlp.118/) (StATA-QE variant).
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It achieves an RMSE loss of 0.36 on the dev split, and a Pearson correlation of 0.59 with human evaluations on the test split ("attributable" column) of [this dataset](https://huggingface.co/datasets/adenhaus/stata).
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# Example use
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This learned metric is for evaluating models trained on the TaTA dataset. It was trained as per instructions in [TaTA: A Multilingual Table-to-Text Dataset for African Languages](https://aclanthology.org/2023.findings-emnlp.118/) (StATA-QE variant).
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The original file can be found [here](https://github.com/google-research/url-nlp/tree/main/tata).
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It achieves an RMSE loss of 0.36 on the dev split, and a Pearson correlation of 0.59 with human evaluations on the test split ("attributable" column) of [this dataset](https://huggingface.co/datasets/adenhaus/stata).
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# Example use
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