How to train and test the ALBERT model.

[VikasRajashekar]

I still didn't find the proper documentation on how to train and test the model.

I somehow fixed the training issues using the input from https://github.com/google-research/google-research/issues/84

Now I have the trained check points. But I am not able to test it because of missing vocab.txt. I tried to use vocab.txt from BERT model still failed.

Did any one figure out a way to test the model.

My arguments for training:

!python -m run_classifier_with_tfhub \
  --albert_hub_module_handle=https://tfhub.dev/google/albert_base/1 --task_name=cola --do_train=true --do_eval=true --data_dir=./dataset --output_dir=./albert_output/ --max_seq_length=64  --train_batch_size=2 --learning_rate=2e-5 --num_train_epochs=3.0

My arguments for testing:
!python run_classifier_sp.py --task_name=cola --do_predict=true --data_dir=./dataset --albert_config_file=./model/2/assets/albert_config.json --init_checkpoint=./albert_output/model.ckpt-906 --vocab_file=./model/vocab.txt --max_seq_length=64 --output_dir=./albert_output/

[0x0539]

Sorry for the delay.
Updated instructions for pretraining and fine tuning are in the readme.
Please reopen if you still have issues.