Comments (2)
Hello gahdritz, any luck in finding a solution for this problem?
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@gahdritz Sorry for the delay on answering this -- I missed it. The T5 tokenizer is just for English so cannot reliably handle other languages/scripts. The Flan Collection does include multiple languages (especially within the NIv2 submixture), but we did not exclude this training data in our runs (either for Flan-T5 or Flan-PaLM, where the latter is multilingual).
To accommodate multilingual datasets you can either change the tokenizer used in the Flan Collection, or just save the pretokenized inputs and outputs yourself and tokenize them later.
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Related Issues (20)
- Datafile AESLC-master.zip meet non_matching_checksum_error
- Broken Dataset Links in FLAN Repository HOT 1
- Question about data source splits
- Trying to access `splits['train']` but `splits` is empty
- Reproducing the flan_v2 results of T5-xl HOT 3
- Code for mixing Enrico sets? HOT 2
- Thank you for your efforts. This is a great job!I have a problem. Why is there only 70 tasks in this FLAN2021_submix_original, and it seems that there are over 140 in the paper? HOT 1
- Could you share the training loss to improve reproducibility? HOT 4
- [Question] Training data formatting for other custom models
- Questions about the Flan Held-Out Tasks (pubmed_qa) and experiment details in the flan collection paper
- Doubt about the TARGET parameter in the dataset
- Issue generating flan2021 submix HOT 1
- Does anyone know which 282 tasks are used? HOT 1
- AESLC Checksum error HOT 4
- No train split in `adversarial_qa_dbert_answer_the_following_q_template_0to10_no_opt_x_shot`
- some Enrico COT entries seem odd HOT 1
- How many samples were used to train Flan-T5?
- Finetuning is definitely better than zero-shot, this is inevitable. So how should I understand the title of this paper?
- Where can I find the test mixture and its templates to reproduce the results in the paper?
- Links to Enrico Shippole FLAN dataset are missing HOT 1
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