language: en | |
thumbnail: https://github.com/junnyu | |
tags: | |
- pytorch | |
- electra | |
- roformer | |
- rotary position embedding | |
license: mit | |
datasets: | |
- openwebtext | |
# 一、 个人在openwebtext数据集上添加rotary-position-embedding,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-RoFormer-Small-OWT (this)**|55.76|90.45|87.3|86.64|89.61|81.17|88.85|62.71|80.31| | |
# 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 50W | |
- GPU RTX3090 | |
- 训练时间总共耗费55h | |
# 四、wandb日志 | |
- [**预训练日志**](https://wandb.ai/junyu/electra_rotary_small_pretrain?workspace=user-junyu) | |
- [**GLUE微调日志**](https://wandb.ai/junyu/electra_rotary_glue_100?workspace=user-junyu) | |
# 五、 使用 | |
```python | |
import torch | |
from transformers import ElectraTokenizer,RoFormerModel | |
tokenizer = ElectraTokenizer.from_pretrained("junnyu/roformer_small_discriminator") | |
model = RoFormerModel.from_pretrained("junnyu/roformer_small_discriminator") | |
inputs = tokenizer("Beijing is the capital of China.", return_tensors="pt") | |
with torch.no_grad(): | |
outputs = model(**inputs) | |
print(outputs[0].shape) | |
``` |