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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/).
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It achieves an RMSE loss of 0.41 on the dev split, and a Pearson correlation of 0.23 with human evaluations on the test split ("attributable" column of [this dataset](https://huggingface.co/datasets/adenhaus/stata)).
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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 0.41 on the dev split, and a Pearson correlation of 0.23 with human evaluations on the test split ("attributable" column of [this dataset](https://huggingface.co/datasets/adenhaus/stata)).
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