PyTorch
Safetensors
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  ProX models are evaluated over 10 language model benchmarks in zero-shot setting.
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- | | ARC-C | ARC-E | CSQA | HellaS | MMLU | OBQA | PiQA | SIQA | WinoG | SciQ | AVG |
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  |-----------------------|-------|-------|-------|-----------|-------|-------|-------|-------|-------|-------|------|
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  | raw | 22.6% | 41.9% | 29.7% | 32.8% | 26.2% | 26.4% | 62.2% | 39.3% | 51.3% | 63.3% | 39.6 |
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  | ours | 25.9% | 47.5% | 29.2% | 36.7% | 28.1% | 30.2% | 64.6% | 38.0% | 51.7% | 71.4% | 42.3 |
 
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  ProX models are evaluated over 10 language model benchmarks in zero-shot setting.
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+ | | ArC-c | ARC-e | CSQA | HellaS | MMLU | OBQA | PiQA | SIQA | WinoG | SciQ | AVG |
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  |-----------------------|-------|-------|-------|-----------|-------|-------|-------|-------|-------|-------|------|
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  | raw | 22.6% | 41.9% | 29.7% | 32.8% | 26.2% | 26.4% | 62.2% | 39.3% | 51.3% | 63.3% | 39.6 |
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  | ours | 25.9% | 47.5% | 29.2% | 36.7% | 28.1% | 30.2% | 64.6% | 38.0% | 51.7% | 71.4% | 42.3 |