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| Model | CoLA | SST | MRPC | STS | QQP | MNLI | QNLI | RTE | Avg. |
|---|---|---|---|---|---|---|---|---|---|
| Metrics | MCC | Acc | Acc | Spearman | Acc | Acc | Acc | Acc | |
| ELECTRA-Small-OWT(original) | 56.8 | 88.3 | 87.4 | 86.8 | 88.3 | 78.9 | 87.9 | 68.5 | 80.36 |
| ELECTRA-Small-OWT (this) | 55.82 | 89.67 | 87.0 | 86.96 | 89.28 | 80.08 | 87.50 | 66.07 | 80.30 |
1import torch
2from transformers.models.electra import ElectraModel, ElectraTokenizer
3tokenizer = ElectraTokenizer.from_pretrained("junnyu/electra_small_discriminator")
4model = ElectraModel.from_pretrained("junnyu/electra_small_discriminator")
5inputs = tokenizer("Beijing is the capital of China.", return_tensors="pt")
6with torch.no_grad():
7 outputs = model(**inputs)
8 print(outputs[0].shape)