The cleaned dataset appears to hallucinate less and perform better than the original dataset. Alpaca is a fine-tuned version of LLAMA that was trained using an Instruct Dataset generated by GPT-3. The generated dataset was designed to bediverse; however, recent analysis indicates it is very US...
从上面可以看到,在一台8卡的A800服务器上面,基于Alpaca-Lora针对alpaca_data_cleaned.json指令数据大概20分钟左右即可完成参数高效微调,相对于斯坦福羊驼训练速度显著提升。 参考文档: LLaMA Stanford Alpaca:斯坦福-羊驼 Alpaca-LoRA 审核编辑 :李倩
Stanford Alpaca中的alpaca_data.json文件即是他们用于训练的指令数据集,我们可以直接使用该数据集进行模型精调。但是在Alpaca-LoRA中提到该数据集存在一些噪声,因此,他们对该数据集做了清洗后得到了alpaca_data_cleaned.json文件。采用该数据集进行训练大概率会得到更好结果。 模型精调 Stanford Alpaca 使用 Hugging Fac...
If you have your own instruction tuning dataset, editDATA_PATHinfinetune.pyto point to your own dataset. Make sure it has the same format asalpaca_data_cleaned.json. Run the fine-tuning script: cog run python finetune.py This takes 3.5 hours on a 40GB A100 GPU, and more than that fo...
可以搞个我们自己的shareGPT,老外整天顾忌白左那些乱七八糟的价值观,还是我们自己来方便一点。我估计很快就会有人搞出来。你的REPO我老早就看到了,非常有前途,我始终觉得只要数据量足够,不管是用老办法还是transformer还是别的什么都能达成目的。所以最关键的点其实还是数据说到底。 2023-04-05· 浙江 回复6...
If you have your own instruction tuning dataset, edit DATA_PATH in finetune.py to point to your own dataset. Make sure it has the same format as alpaca_data_cleaned.json. Run the fine-tuning script: cog run python finetune.py This takes 3.5 hours on a 40GB A100 GPU, and more than...
A cleaner dataset The original dataset contains a number of bad data points, so people have been cleaning it. The description of thecleaned versionprovides examples of what needed corrections. Further, they added a whole similardataset distilled from GPT-4. The instructions are the same, the res...
{ "args": [ "--base_model", "yahma/llama-7b-hf", "--num_epochs=10", "--data_path", "yahma/alpaca-cleaned", "--output_dir", "./your output dir", "--cutoff_len=512", "--lora_target_modules=[q_proj,k_proj,v_proj,o_proj]", "--lora_r=16", "--micro_batch_size=...
This model is a fine-tuned version of the Gemma 2B (GemmaCausalLM) model, specifically adapted for instruction-based tasks using the Alpaca Cleaned dataset. The fine-tuning process employs the Low-Rank Adaptation (LoRA) method, which allows for efficient parameter updates while maintaining the com...
The cleaned dataset appears to hallucinate less and perform better than the original dataset. Alpaca is a fine-tuned version of LLAMA that was trained using an Instruct Dataset generated by GPT-3. The generated dataset was designed to bediverse; however, recent analysis indicates it is very US...