Comments (5)
We use Karpathy et al. split for COCO, and the code of Oscar repo
For conceptual captions we use the validation set as the test set wasn't released and require evaluation on Google Cloud, but we didn't use the validation set for validation purposes at all.
Hope it helps
@amirhertz
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@rmokady Thank you for answering!
Where can I find details about the karpathy split, how each data split is created? I saw you uploaded the train_captions but not val/test captions
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We just use the same split as used in Oscar repo
You can run their inference script which will produce a json with test captions
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We just use the same split as used in Oscar repo
You can run their inference script which will produce a json with test captions
Could you please share your val/test captions? I'm having some difficulty running Oscar.
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我们只使用与 Oscar 存储库中使用的相同的分割
您可以运行他们的推理脚本,该脚本将生成带有测试标题的 json您能分享您的验证/测试标题吗?我在竞选奥斯卡时遇到了一些困难。
请问您解决了吗这个我呢提,我也遇到了这个问题
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Related Issues (20)
- Some questions about fine-tune with custom dataset HOT 8
- AttributeError: module 'cog' has no attribute 'Predictor' HOT 3
- model overfitting issue HOT 5
- Parsing conceptual caption does not function properly as it removes some images and replaces them with zero tensor. HOT 1
- use different encoder HOT 3
- How to evaluate model with meteor, BLEU, or rouge HOT 3
- AttributeError: module 'cog' has no attribute 'Predictor' HOT 2
- Train costom data HOT 1
- Metrics of ClipCap's Original Performance HOT 2
- use multiple gpus to train
- How to evaluate the trained model? Is there a test.py ? HOT 6
- did anyone reproduce the transformer network with frozen GPT-2? HOT 7
- data json
- Where is the file 'model_wieghts.pt' exists?
- How to do eval, how to set the prompt
- How to inference after training on my own dataset HOT 1
- beamsearch lead to a worse result in inference script?
- Error in Load model weights HOT 3
- clipcap checkpoints file
- Can BERT be used as language model for generating captions? HOT 1
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