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tunib
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electra-ko-base

Transformers PyTorch electra pretraining Inference Endpoints
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@@ -31,11 +31,11 @@ model = AutoModel.from_pretrained('tunib/electra-ko-base')
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  | |**# Params** |**Avg.**| **NSMC**<br/>(acc) | **Naver NER**<br/>(F1) | **PAWS**<br/>(acc) | **KorNLI**<br/>(acc) | **KorSTS**<br/>(spearman) | **Question Pair**<br/>(acc) | **KorQuaD (Dev)**<br/>(EM/F1) |**Korean-Hate-Speech (Dev)**<br/>(F1)|
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  | :----------------:| :----------------: | :--------------------: | :----------------: | :------------------: | :-----------------------: | :-------------------------: | :---------------------------: | :---------------------------: | :---------------------------: | :----------------: |
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- |***TUNiB-Electra-ko-base*** | 110M | **85.99** | 90.95 | 87.63 | **84.65** | **82.27** | 85.00 | 95.77 | 64.01 / 90.32 |71.40 |
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- |***TUNiB-Electra-ko-en-base*** | 133M |84.74 |90.15 | 86.93 | 83.05 | 79.70 | 82.23 | 95.64 | 83.61 / 92.37 |67.86 |
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  | [KoELECTRA-base-v3](https://github.com/monologg/KoELECTRA) | 110M | 85.92 |90.63 | **88.11** | 84.45 | 82.24 | **85.53** | 95.25 | **84.83 / 93.45** | 67.61 |
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  | [KcELECTRA-base](https://github.com/Beomi/KcELECTRA) | 124M| 84.75 |**91.71** | 86.90 | 74.80 | 81.65 | 82.65 | **95.78** | 70.60 / 90.11 | **74.49** |
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- | [KoBERT-base](https://github.com/SKTBrain/KoBERT) | 90M | 81.92 | 89.63 | 86.11 | 80.65 | 79.00 | 79.64 | 93.93 | 52.81 / 80.27 | 66.21 |
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- | [KcBERT-base](https://github.com/Beomi/KcBERT) | 110M | 79.79 | 89.62 | 84.34 | 66.95 | 74.85 | 75.57 | 93.93 | 60.25 / 84.39 | 68.77 |
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- | [XLM-Roberta-base](https://github.com/pytorch/fairseq/tree/master/examples/xlmr) | 280M | 83.03 |89.49 | 86.26 | 82.95 | 79.92 | 79.09 | 93.53 | 64.70 / 88.94 | 64.06 |
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  | |**# Params** |**Avg.**| **NSMC**<br/>(acc) | **Naver NER**<br/>(F1) | **PAWS**<br/>(acc) | **KorNLI**<br/>(acc) | **KorSTS**<br/>(spearman) | **Question Pair**<br/>(acc) | **KorQuaD (Dev)**<br/>(EM/F1) |**Korean-Hate-Speech (Dev)**<br/>(F1)|
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  | :----------------:| :----------------: | :--------------------: | :----------------: | :------------------: | :-----------------------: | :-------------------------: | :---------------------------: | :---------------------------: | :---------------------------: | :----------------: |
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+ |***TUNiB-Electra-ko-base*** | 110M | **85.99** | 90.95 | 87.63 | 84.65 | **82.27** | 85.00 | 95.77 | 64.01 / 90.32 |71.40 |
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+ |***TUNiB-Electra-ko-en-base*** | 133M |85.34 |90.59 | 87.25 | **84.90** | 80.43 | 83.81 | 94.85 | 83.09 / 92.06 |68.83 |
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  | [KoELECTRA-base-v3](https://github.com/monologg/KoELECTRA) | 110M | 85.92 |90.63 | **88.11** | 84.45 | 82.24 | **85.53** | 95.25 | **84.83 / 93.45** | 67.61 |
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  | [KcELECTRA-base](https://github.com/Beomi/KcELECTRA) | 124M| 84.75 |**91.71** | 86.90 | 74.80 | 81.65 | 82.65 | **95.78** | 70.60 / 90.11 | **74.49** |
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+ | [KoBERT-base](https://github.com/SKTBrain/KoBERT) | 90M | 84.17 | 89.63 | 86.11 | 80.65 | 79.00 | 79.64 | 93.93 | 52.81 / 80.27 | 66.21 |
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+ | [KcBERT-base](https://github.com/Beomi/KcBERT) | 110M | 81.37 | 89.62 | 84.34 | 66.95 | 74.85 | 75.57 | 93.93 | 60.25 / 84.39 | 68.77 |
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+ | [XLM-Roberta-base](https://github.com/pytorch/fairseq/tree/master/examples/xlmr) | 280M | 85.74 |89.49 | 86.26 | 82.95 | 79.92 | 79.09 | 93.53 | 64.70 / 88.94 | 64.06 |
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