This is a t5-small fine-tuned version on the math_dataset/measurement_time for solving measurement time equations mission.

To load the model: (necessary packages: !pip install transformers sentencepiece)

from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("dbernsohn/t5_measurement_time")
model = AutoModelWithLMHead.from_pretrained("dbernsohn/t5_measurement_time")

You can then use this model to solve algebra 1d equations into numbers.

query = "How many minutes are there between 2:09 PM and 2:27 PM?"
input_text = f"{query} </s>"
features = tokenizer([input_text], return_tensors='pt')
model.to('cuda')
output = model.generate(input_ids=features['input_ids'].cuda(), 
                        attention_mask=features['attention_mask'].cuda())

tokenizer.decode(output[0])
# <pad> 18</s>

Another examples:

  • How many minutes are there between 2:09 PM and 2:27 PM?
  • Answer: 18 Pred: 18

  • What is 116 minutes after 10:06 AM?
  • Answer: 12:02 PM Pred: 12:02 PM

  • What is 608 minutes after 3:14 PM?
  • Answer: 1:22 AM Pred: 1:22 AM

  • What is 64 minutes before 9:16 AM?
  • Answer: 8:12 AM Pred: 8:12 AM

  • What is 427 minutes before 4:27 AM?
  • Answer: 9:20 PM Pred: 9:20 PM

  • How many minutes are there between 6:36 PM and 12:15 AM?
  • Answer: 339 Pred: 339

  • What is 554 minutes before 5:24 PM?
  • Answer: 8:10 AM Pred: 8:10 AM

  • What is 307 minutes after 5:15 AM?
  • Answer: 10:22 AM Pred: 10:22 AM

The whole training process and hyperparameters are in my GitHub repo

Created by Dor Bernsohn

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Select AutoNLP in the “Train” menu to fine-tune this model automatically.

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