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Add How to Reproduce the Result in README #2
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@gentaiscool : I think we need to change the load_model
and clean up the unused model checkpoints that are used for our experiment. We can instead use Indobenchmark model in HF as the replacement. Can you help to clean that part?
@atnanahidiw, later you can follow the checkpoint argument based on the finalized models that we have. So it will be cleaner and easier to follow.
I will clean the code and add the documentation this week including the CONTRIBUTING page. Let's finish the testing and then, we merge this pull request. |
I added the CONTRIBUTING page in the |
@atnanahidiw we just merged the master branch with a new PR #7. Would you mind to check whether this PR has any conflict? |
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hi @gentaiscool, I just resolved all of the conflicts ya, sorry for the late reply 🙏 |
and thanks also for the CONTRIBUTING page |
Yes, we should, probably in a new PR? |
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@atnanahidiw : We have some update regarding to the model list, can you help removing the unnecessary models and adding the IndoBERT model. I write the comment for all the models that can be removed and also the list of IndoBERT models.
# lower: | ||
# num_layers: | ||
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# # albert-base-uncased-96000 |
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This model can be removed
# num_layers: | ||
# - 12 | ||
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# # albert-base-uncased-96000-spm |
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This model can be removed
# - 12 | ||
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# # albert-base-uncased-96000-spm | ||
# - model_checkpoint: albert-base-uncased-96000-spm |
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This model can be removed
# num_layers: | ||
# - 12 | ||
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# # albert-base-uncased-112500-spm |
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This model can be removed
# - 12 | ||
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# scratch | ||
- model_checkpoint: scratch |
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This model can be removed
- 24 | ||
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# babert-bpe-mlm-large-uncased-1100k | ||
- model_checkpoint: babert-bpe-mlm-large-uncased-1100k |
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This model can be removed
- 24 | ||
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# babert-bpe-mlm-uncased-128-dup10-5 | ||
- model_checkpoint: babert-bpe-mlm-uncased-128-dup10-5 |
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This model can be removed
python3 scripts/reproducer.py term-extraction-airy 15 $(BATCH_SIZE) $(HYPERPARAMETER) | ||
python3 scripts/reproducer.py pos-prosa 15 $(BATCH_SIZE) $(HYPERPARAMETER) | ||
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reproduce_all_1: |
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We can remove reproduce_all_*
, it is already covered in reproduce
and reproduce_all
for this
run_non_pretrained_no_special_token: | ||
python3 scripts/reproducer_non_pretrained.py $(DATASET) $(EARLY_STOP) $(BATCH_SIZE) | ||
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run_non_pretrained_no_special_token_all: |
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There are 8 tasks in here, can you please help adding the other 4 similar to the list in the reproduce_all
?
- model_checkpoint: babert-bpe-mlm-uncased-128-dup10-5 | ||
lower: True | ||
num_layers: | ||
- 12 |
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Can you help adding 8 indoBERT models in this file, the model checkpoint and the num_layers would be as follow:
- indobenchmark/indobert-base-p1 | 12 layers
- indobenchmark/indobert-base-p2 | 12 layers
- indobenchmark/indobert-large-p1 | 24 layers
- indobenchmark/indobert-large-p2 | 24 layers
- indobenchmark/indobert-lite-base-p1 | 12 layers
- indobenchmark/indobert-lite-base-p2 | 12 layers
- indobenchmark/indobert-lite-large-p1 | 24 layers
- indobenchmark/indobert-lite-large-p2 | 24 layers
Yeah I agree, this one can be a new PR. Thank you 😀 |
Refactor:
run_single_task.sh
run_all_tasks.sh
run_non_pretrained_no_special_token.sh
by:
scripts/config/model/train.yaml
to easily define the model usedscripts/reproducer.py
andMakefile
for easy opsNote: only tested this by printing the command string, sorry 🙏