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Hi, I'm trying to reproduce the results for the repo for the supervised training and am using the following environment:
V100 (p3.2xlage) Transformers 4.2.1 PyTorch 1.12 CUDA Version: 11.3
When using these settings I get the following results:
Bert-base-uncased ------ test ------ | STS12 | STS13 | STS14 | STS15 | STS16 | STSBenchmark | SICKRelatedness | Avg. | | 74.46 | 83.81 | 79.25 | 86.02 | 81.07 | 84.00 | 80.65 | 81.32 |
Roberta-base ------ test ------ | STS12 | STS13 | STS14 | STS15 | STS16 | STSBenchmark | SICKRelatedness | Avg. | | 76.23 | 86.07 | 80.71 | 86.72 | 83.32 | 85.95 | 80.24 | 82.75 |
It looks like the results are slightly off compared to the reported ones, can you please share the Pytorch and Cuda versions used for training?
Thanks!
The text was updated successfully, but these errors were encountered:
Hi, these are the Pytorch and Cuda versions we use: Nvidia RTX 3090Ti GPUs Transformers 4.2.1 PyTorch 1.10 CUDA Version: 11.4
Results can vary based on different hardware/software.
Sorry, something went wrong.
Are you able to release the checkpoints for sup-PromCSE-RoBERTa-base? I cannot reproduce results due to hardware differences I presume. Thanks
Hi, the checkpoint for sup-PromCSE-RoBERTa-base has been uploaded to Huggingface (https://huggingface.co/YuxinJiang/sup-promcse-roberta-base). I hope this helps you :)
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Hi, I'm trying to reproduce the results for the repo for the supervised training and am using the following environment:
V100 (p3.2xlage)
Transformers 4.2.1
PyTorch 1.12
CUDA Version: 11.3
When using these settings I get the following results:
Bert-base-uncased
------ test ------
| STS12 | STS13 | STS14 | STS15 | STS16 | STSBenchmark | SICKRelatedness | Avg. |
| 74.46 | 83.81 | 79.25 | 86.02 | 81.07 | 84.00 | 80.65 | 81.32 |
Roberta-base
------ test ------
| STS12 | STS13 | STS14 | STS15 | STS16 | STSBenchmark | SICKRelatedness | Avg. |
| 76.23 | 86.07 | 80.71 | 86.72 | 83.32 | 85.95 | 80.24 | 82.75 |
It looks like the results are slightly off compared to the reported ones, can you please share the Pytorch and Cuda versions used for training?
Thanks!
The text was updated successfully, but these errors were encountered: