Comments (1)
感谢对我们工作的关注,您观察非常细致。
- Table3的ablation的训练数据只用了cc3m ,而Table1 的数据集用的是36m的数据量,所以Table3中模型的效果会比Table1中的低。
- Table1中AltCLIP进行了Teacher learning 和Contrastive learning 两个stage的学习,经过学习后英文imagenet zero-shot稍微降低74.7->74.5,但是中文imagenet zero-shot显著提升58.2->59.6,而Table3 中AltCLIP_T只经过了teacher learning的学习。
- 我们后续会release相关的benchmark代码,敬请期待。
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Related Issues (20)
- [Question]: 如何进行模型并行训练 HOT 2
- 怎么加载altclip模型? HOT 5
- [Question]: Lora微调 HOT 3
- [Question]: modehub中的altclip与huggingface上的altclip参数不一致 HOT 4
- [Question]: UnboundLocalError: local variable 'model_id' referenced before assignment
- [Question]: Model hub is not reachable! HOT 4
- [Question]: altclip直接运行example的inference.py报错KeyError: 'text_config' HOT 2
- [Question]: How to train the altclip model
- AquilaChat2 34B推理问题 HOT 1
- [Question]: 使用flagai AutoLoader加载AquilaChat2-7B-16K,输入英文 输出乱码 HOT 2
- 运行对话脚本aquilachat2-34b-16k 报错误 HOT 1
- Collecting PyYAML==5.4.1 (from flagai)报错 HOT 4
- [Question]: No module named 'packaging' This question is after install NVIDIA's apex HOT 1
- torchrun command not found HOT 5
- [Question]: 想问下AquilaDecoderLayer里的传参为什么是float的?这样是用的float类型的attention HOT 2
- Can't run examples/vit_cifar100/train_deepspeed.py HOT 1
- TypeError: AquilaPreTrainedModel._set_gradient_checkpointing() got an unexpected keyword argument 'enable' HOT 2
- How does one obtain training data suitable for fine-tuning Aquila models? HOT 2
- [Question]: 请问AltCLIP有没有提供使用Flickr30k微调及评估的脚本
- Do you have this dataset?[Question]:
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