Comments (2)
Seems like it's converged, have you evaluated the held out perplexity for this model? FWIW, the training perplexity can be noisy from batch to batch, so I've found it useful to load the tensorboard checkpoint and use the smoothing function to quickly visually check for convergence.
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Average held out perplexity seems to be close to what you report in the paper (around 36) so it has indeed converged. Would be nice to add some indications on how to verify that the model is training correctly in the README or somewhere to make it easier to replicate results. Thanks for your help!
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Related Issues (20)
- UnicodeError when run example: python -m unittest discover tests/ HOT 2
- how many time it takes if I training a 5GB corpus on 1080ti
- How to use ELMo in Keras version? HOT 1
- why should vocabulary file be sorted in descending order by token count in our training data๏ผ
- bug during data loading (and tests) HOT 2
- Training ELMO on TPU for generating embedding from custom dataset
- how to freeze some layers during training HOT 1
- Import Error: No module named bilm.training when I try to incrementally train ELMo HOT 1
- drastic impact of Changing the vocabulary on perplexity HOT 1
- incremental training on less than 2000 sentences HOT 2
- elmo sentence embeddings using usage_token.py
- The PyTorch version replication of the "Deep contextualized word representations" is missing
- Does any code about ELMO+ESIM? HOT 1
- Exporting finetuned model to SavedModel format for Tensorflow Serving HOT 6
- Compute training time
- Preparing training data for a domain with many multi keyword token HOT 1
- Running into error on tests HOT 3
- Saving the custom trained ELMO embedding (hdf5) in the format of tensorhub models
- 2021-10-29 14:13:30.313623: E C:\users\nwani\_bazel_nwani\mmtm6wb6\execroot\org_tensorflow\tensorflow\stream_executor\cuda\cuda_event.cc:49] Error polling for event status: failed to query event: CUDA_ERROR_OUT_OF_MEMORY
- Pre-trained links do not work HOT 7
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