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@@ -87,6 +87,19 @@ The training was done on a single 16GB NVIDIA Tesla V100 GPU. For MRPC/WNLI, the
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  The following table summarizes the results for [fnet-base](https://huggingface.co/google/fnet-base) (called *FNet (PyTorch) - Reproduced*) and [bert-base-cased](https://hf.co/models/bert-base-cased) (called *Bert (PyTorch) - Reproduced*) in terms of training times. The format is *hour:min:seconds*.
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  | Task | MNLI-(m/mm) | QQP | QNLI | SST-2 | CoLA | STS-B | MRPC | RTE | WNLI | SUM |
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  |:----:|:-----------:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:|:----:|:-------:|
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  |FNet-base (PyTorch)| [06:40:55](https://huggingface.co/gchhablani/fnet-base-finetuned-mnli)| [06:21:16](https://huggingface.co/gchhablani/fnet-base-finetuned-qqp) | [01:48:22](https://huggingface.co/gchhablani/fnet-base-finetuned-qnli) | [01:09:27](https://huggingface.co/gchhablani/fnet-base-finetuned-sst2) | [00:09:47](https://huggingface.co/gchhablani/fnet-base-finetuned-cola) | [00:07:09](https://huggingface.co/gchhablani/fnet-base-finetuned-stsb) | [00:07:48](https://huggingface.co/gchhablani/fnet-base-finetuned-mrpc) | [00:03:24](https://huggingface.co/gchhablani/fnet-base-finetuned-rte) | [00:02:37](https://huggingface.co/gchhablani/fnet-base-finetuned-wnli) | 16:30:45 |
 
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  The following table summarizes the results for [fnet-base](https://huggingface.co/google/fnet-base) (called *FNet (PyTorch) - Reproduced*) and [bert-base-cased](https://hf.co/models/bert-base-cased) (called *Bert (PyTorch) - Reproduced*) in terms of training times. The format is *hour:min:seconds*.
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+ | Task/Model | FNet-base (PyTorch) |Bert-base (PyTorch)|
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+ | MNLI-(m/mm) | [06:40:55](https://huggingface.co/gchhablani/fnet-base-finetuned-mnli) | [09:52:33](https://huggingface.co/gchhablani/bert-base-cased-finetuned-mnli)|
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+ | QQP | [06:21:16](https://huggingface.co/gchhablani/fnet-base-finetuned-qqp) | [09:25:01](https://huggingface.co/gchhablani/bert-base-cased-finetuned-qqp) |
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+ | QNLI | [01:48:22](https://huggingface.co/gchhablani/fnet-base-finetuned-qnli) | [02:40:22](https://huggingface.co/gchhablani/bert-base-cased-finetuned-qnli)|
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+ | SST-2 | [01:09:27](https://huggingface.co/gchhablani/fnet-base-finetuned-sst2) | [01:42:17](https://huggingface.co/gchhablani/bert-base-cased-finetuned-sst2)|
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+ | CoLA | [00:09:47](https://huggingface.co/gchhablani/fnet-base-finetuned-cola) | [00:14:20](https://huggingface.co/gchhablani/bert-base-cased-finetuned-cola)|
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+ | STS-B | [00:07:09](https://huggingface.co/gchhablani/fnet-base-finetuned-stsb) | [00:10:24](https://huggingface.co/gchhablani/bert-base-cased-finetuned-stsb)|
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+ | MRPC | [00:07:48](https://huggingface.co/gchhablani/fnet-base-finetuned-mrpc) | [00:11:12](https://huggingface.co/gchhablani/bert-base-cased-finetuned-mrpc)|
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+ | RTE | [00:03:24](https://huggingface.co/gchhablani/fnet-base-finetuned-rte) | [00:04:51](https://huggingface.co/gchhablani/bert-base-cased-finetuned-rte)|
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+ | WNLI | [00:02:37](https://huggingface.co/gchhablani/fnet-base-finetuned-wnli) | [00:03:23](https://huggingface.co/gchhablani/bert-base-cased-finetuned-wnli)|
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+ | SUM | 16:30:45 | 24:23:56 |
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  | Task | MNLI-(m/mm) | QQP | QNLI | SST-2 | CoLA | STS-B | MRPC | RTE | WNLI | SUM |
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  |:----:|:-----------:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:|:----:|:-------:|
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  |FNet-base (PyTorch)| [06:40:55](https://huggingface.co/gchhablani/fnet-base-finetuned-mnli)| [06:21:16](https://huggingface.co/gchhablani/fnet-base-finetuned-qqp) | [01:48:22](https://huggingface.co/gchhablani/fnet-base-finetuned-qnli) | [01:09:27](https://huggingface.co/gchhablani/fnet-base-finetuned-sst2) | [00:09:47](https://huggingface.co/gchhablani/fnet-base-finetuned-cola) | [00:07:09](https://huggingface.co/gchhablani/fnet-base-finetuned-stsb) | [00:07:48](https://huggingface.co/gchhablani/fnet-base-finetuned-mrpc) | [00:03:24](https://huggingface.co/gchhablani/fnet-base-finetuned-rte) | [00:02:37](https://huggingface.co/gchhablani/fnet-base-finetuned-wnli) | 16:30:45 |