Hi,
I am trying to fine-tune a model to extract custom data from a sentence. The data looks like this:




text
target




We are open from 8 am to 6 pm
8-6


The store working hours are 8-8
8-8


Some random text
none



I tried to fine-tune the T5 base to do this task but the generated text didn’t follow the custom dataset.
Steps I followed:

Load T5ForConditionalGeneration and T5Tokenizer.
Load my custom dataset.
Tokenize the text data with a prefix for tokenizer “extract working hours:”.
Train using Trainer.
Save the model locally.
Load model.
Apply transformers pipeline to generate text.

I also tried to use a custom function to tokenize the input and decode output instead of using the pipeline, which didn’t generate the expected output.
Next, I copied Fine Tuning T5 Transformer Model with PyTorch colab notebook and replaced the dataset with mine. The generated text wasn’t correct either.
Is T5 the right model for what I am trying to achieve? If not, which model would you recommend for this task?
Thank you!