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Update README.md
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README.md
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@@ -121,9 +121,9 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
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| MiniLMv2-L6-H768-from-RoBERTa-Large | 81,529,346 | 4:39:02 | 9:34 | 1:06 | 65.80 | 77.17 | 51.72 | 63.27 |
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| RoBERTa-Base | 124,056,578 | 8:50:29 | 18:59 | 2:11 | 69.06 | 80.08 | 55.53 | 66.49 |
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| RoBERTa-Large | 354,312,194 | 29:16:06 | 1:01:10 | 7:04 | 74.08 | 84.38 | 62.20 | 72.88 |
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|TinyRoBERTa | 81,529.346 | 4:27:06
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# Limitations and Bias
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| MiniLMv2-L6-H768-from-RoBERTa-Large | 81,529,346 | 4:39:02 | 9:34 | 1:06 | 65.80 | 77.17 | 51.72 | 63.27 |
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| RoBERTa-Base | 124,056,578 | 8:50:29 | 18:59 | 2:11 | 69.06 | 80.08 | 55.53 | 66.49 |
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| RoBERTa-Large | 354,312,194 | 29:16:06 | 1:01:10 | 7:04 | 74.08 | 84.38 | 62.20 | 72.88 |
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|TinyRoBERTa | 81,529.346 | 4:27:06 *| 9:54 | 1:04 | 69.38 | 80.07| 53.29| 64.16|
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\*: Training times aren't perfectly comparable as TinyRoBERTa was distilled from [VMware/roberta-large-mrqa](https://huggingface.co/VMware/roberta-large-mrqa) that was already trained on MRQA
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# Limitations and Bias
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