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update readme

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hiyouga 2023-11-18 11:15:56 +08:00
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@ -43,9 +43,9 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
![benchmark](assets/benchmark.svg)
- Training Speed: the number of training samples processed per second during the training. (bs=4, cutoff_len=1024)
- BLEU Score: BLEU-4 score on the development set of the [advertising text generation](https://aclanthology.org/D19-1321.pdf) task. (bs=4, cutoff_len=1024)
- GPU Memory: Peak GPU memory usage in the 4-bit quantized training. (bs=1, cutoff_len=1024)
- **Training Speed**: the number of training samples processed per second during the training. (bs=4, cutoff_len=1024)
- **BLEU Score**: BLEU-4 score on the development set of the [advertising text generation](https://aclanthology.org/D19-1321.pdf) task. (bs=4, cutoff_len=1024)
- **GPU Memory**: Peak GPU memory usage in 4-bit quantized training. (bs=1, cutoff_len=1024)
- We adopt `pre_seq_len=128` for ChatGLM's P-Tuning and `lora_rank=32` for LLaMA-Factory's LoRA tuning.
## Changelog

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README_zh.md
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@ -43,9 +43,9 @@ https://github.com/hiyouga/LLaMA-Factory/assets/16256802/6ba60acc-e2e2-4bec-b846
![benchmark](assets/benchmark.svg)
- Training Speed: 训练阶段每秒处理的样本数量。（批处理大小=4，截断长度=1024）
- BLEU Score: [广告文案生成](https://aclanthology.org/D19-1321.pdf)任务验证集上的 BLEU-4 分数。（批处理大小=4，截断长度=1024）
- GPU Memory: 4 比特量化训练的 GPU 显存峰值。（批处理大小=1，截断长度=1024）
- **Training Speed**: 训练阶段每秒处理的样本数量。（批处理大小=4，截断长度=1024）
- **BLEU Score**: [广告文案生成](https://aclanthology.org/D19-1321.pdf)任务验证集上的 BLEU-4 分数。（批处理大小=4，截断长度=1024）
- **GPU Memory**: 4 比特量化训练的 GPU 显存峰值。（批处理大小=1，截断长度=1024）
- 我们在 ChatGLM 的 P-Tuning 中采用 `pre_seq_len=128`，在 LLaMA-Factory 的 LoRA 微调中采用 `lora_rank=32`。
## 更新日志