一、 个人在openwebtext数据集上训练得到的electra-small模型
二、 复现结果(dev dataset)
Model |
CoLA |
SST |
MRPC |
STS |
QQP |
MNLI |
QNLI |
RTE |
Avg. |
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 |
三、 训练细节
- 数据集 openwebtext
- 训练batch_size 256
- 学习率lr 5e-4
- 最大句子长度max_seqlen 128
- 训练total step 62.5W
- GPU RTX3090
- 训练时间总共耗费2.5天
四、 使用
from transformers import pipeline
fill_mask = pipeline(
"fill-mask",
model="junnyu/electra_small_generator",
tokenizer="junnyu/electra_small_generator"
)
print(
fill_mask("HuggingFace is creating a [MASK] that the community uses to solve NLP tasks.")
)