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Source code for Dialogue State Tracking with a Language Model using Schema-Driven Prompting
Hello! I'm very interested in your work. So I wanna know when the code will be released.
Hi,
I am trying to use eval.py
, but I am experiencing an error that the file cannot be found. (example below)
FileNotFoundError: [Errno 2] No such file or directory: 'multiwoz/data/MultiWOZ_2.2/test/schema.json'
MultiWOZ official git does not have the schema.json
in data/MultiWOZ_2.2/test, data/MultiWOZ_2.2/train
So I wonder if you use a customized Schema.json files for test and train dataset.
If So, could you share the customized schema file?
Or just brief Schema information will help.
I am grateful for your great work.
I look forward to hearing from you
Regards,
Yeseul
Hi,
Congrats on being accepted in EMNLP 2021 as a concise and solid work! I am currently following your research and trying to reproduce the experimental results in the original paper using your codes. However, I have met some trouble in aligning the same JGA scores.
My experiments were all on MultiWOZ v2.2, with domain and slot descriptions. Here are my hyperparameter settings and corresponding results.
I am wondering if there is some other tricks to achieve a better results. If so, is it okay to share? So much appreciated!
Looking forward to your reply :-D
Best
Hi,
Thanks for your great work!
Can you offer the code for preprocess data on MultiWOZ2.1?
Looking forward to your reply.
Best
Hi, thank you for the nice code. It works fine with t5-small.
I also follow the settings for training t5-base in your paper, but the model seems to be not properly trained. The loss when evaluation is much higher than t5-small, and the prediction results are also terrible. I think it is because the hyperparameters I set are still not correct. Can you also provide your script for training on T5-base? Thank you!
This is the script I am using:
CUDA_VISIBLE_DEVICES=0,1 python examples/pytorch/summarization/run_summarization.py
--model_name_or_path google/t5-base
--do_train
--do_predict
--train_file "$DATA_DIR/train.json"
--validation_file "$DATA_DIR/dev.json"
--test_file "$DATA_DIR/test.json"
--source_prefix ""
--output_dir "$OUTPUT_DIR/t5-base-mwoz2.2"
--per_device_train_batch_size=4
--per_device_eval_batch_size=4
--gradient_accumulation_steps 8
--predict_with_generate
--learning_rate 5e-4
--num_train_epochs 2
--text_column="dialogue"
--summary_column="state"
--save_steps=25000
is there any plan to release the code for preprocess data or preprocessed data for sequential decoding?
Hi,
I think this is a very interesting work which is both simple and efficient !
So I truly want the code for further study.
Best for you
Hi,
I think this is a very interesting work and I have two questions want to check:
Looking forward to your reply.
Best
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