Comments (1)
I think you can select the checkpoints around 100000 training steps using the validation data. The number on the paper is out-of-date, the new results is a bit lower and is 0.84 in BLEU. BTW CCD is a pretty bizarre datasets in a way that it easily overfit the training data and the outputs actually require commonsense knowledges. (Diffuseq only achieved BLEU around 1. This means the outputs barely correlate with the labels.)
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Related Issues (20)
- Question about decoder_nll loss HOT 7
- problems met during inference HOT 2
- Question about EMA HOT 4
- most recent .npy schedule file saved before .pt model weight file HOT 9
- The training recipe for SeqDiffuSeq without adaptive noise schedule HOT 11
- About the decoding of Tokenizer. HOT 2
- Initialize model with pre-trained BART HOT 12
- Request to Evaluate code HOT 2
- About the paper results. HOT 1
- Data for wmt14 is missing HOT 3
- 关于训练时间的询问以及是否可以多卡训练的请教 HOT 2
- Hi,How could I get the BLEU score,for example, specific command? HOT 3
- 'TransformerNetModel_encoder_decoder' object has no attribute 'module' HOT 1
- Checkpoints
- Inference Problem
- MBR-DECODE
- Can't run any train script HOT 2
- The self-conditioning part HOT 4
- About Inference Problem
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