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+ ---
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+ language: fr
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+ license: mit
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+ ---
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+
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+ # roberta-base-wechsel-french
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+
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+ Model trained with WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
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+
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+ See the code here: https://github.com/CPJKU/wechsel
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+
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+ And the paper here: https://arxiv.org/abs/2112.06598
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+
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+ ## Performance
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+
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+ ### RoBERTa
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+
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+ | Model | NLI Score | NER Score | Avg Score |
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+ |---|---|---|---|
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+ | `roberta-base-wechsel-french` | **82.43** | **90.88** | **86.65** |
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+ | `camembert-base` | 80.88 | 90.26 | 85.57 |
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+
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+
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+ | Model | NLI Score | NER Score | Avg Score |
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+ |---|---|---|---|
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+ | `roberta-base-wechsel-german` | **81.79** | **89.72** | **85.76** |
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+ | `deepset/gbert-base` | 78.64 | 89.46 | 84.05 |
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+
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+ | Model | NLI Score | NER Score | Avg Score |
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+ |---|---|---|---|
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+ | `roberta-base-wechsel-chinese` | **78.32** | 80.55 | **79.44** |
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+ | `bert-base-chinese` | 76.55 | **82.05** | 79.30 |
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+
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+ | Model | NLI Score | NER Score | Avg Score |
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+ |---|---|---|---|
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+ | `roberta-base-wechsel-swahili` | **75.05** | **87.39** | **81.22** |
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+ | `xlm-roberta-base` | 69.18 | 87.37 | 78.28 |
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+
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+ ### GPT2
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+
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+ | Model | PPL |
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+ |---|---|
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+ | `gpt2-wechsel-french` | **19.71** |
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+ | `gpt2` (retrained from scratch) | 20.47 |
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+
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+ | Model | PPL |
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+ |---|---|
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+ | `gpt2-wechsel-german` | **26.8** |
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+ | `gpt2` (retrained from scratch) | 27.63 |
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+
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+ | Model | PPL |
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+ |---|---|
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+ | `gpt2-wechsel-chinese` | **51.97** |
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+ | `gpt2` (retrained from scratch) | 52.98 |
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+
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+ | Model | PPL |
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+ |---|---|
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+ | `gpt2-wechsel-swahili` | **10.14** |
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+ | `gpt2` (retrained from scratch) | 10.58 |
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+
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+ See our paper for details.
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+
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+ ## Citation
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+
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+ Please cite WECHSEL as
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+
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+ ```
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+ @misc{minixhofer2021wechsel,
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+ title={WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models},
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+ author={Benjamin Minixhofer and Fabian Paischer and Navid Rekabsaz},
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+ year={2021},
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+ eprint={2112.06598},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+ ```
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