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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, 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
Hi,
I think this is a very interesting work and I have two questions want to check:
Looking forward to your reply.
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,
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,
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
is there any plan to release the code for preprocess data or preprocessed data for sequential decoding?
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