Comments (2)
1jiahe
commented on July 29, 2024
Hi, I got the same problem. May I ask whether you resolved this issue? And how? Thanks a lot
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thatmee
commented on July 29, 2024
Hi, I got the same problem and I solve it by adding Truncation=True and max_length=[max_len] in two encode functions:
As far as I can see this is just a warning message to inform you that the input text is too long, but it doesn't affect the training result, only the output is a bit annoying.
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Related Issues (20)
- OSError: Model name 'clue/albert_chinese_tiny' was not found in tokenizers model name list HOT 2
- TypeError: expected str, bytes or os.PathLike object, not NoneType HOT 1
- ZeroDivisionError when reduction is set to 'wmean' while training iPET HOT 1
- Stuck at 'There are 0 Examples for Label [my_label]' During iPETs Example Selection for Next Generation
- There is no softmax
- Training Time Issue HOT 4
- GenPET commands with GPT-2 HOT 2
- RuntimeError on eval method HOT 2
- PET and iPET parameters
- Random seed parameter for iterations
- Data format for few-shot text classification
- Roberta-large using BPE tokenizer generates multi tokens. HOT 6
- API Usage
- How much test data do you use in your experiments?
- How to training PET model uses xlm-roberta with byte-level Byte-Pair-Encoding?
- How to reproduce results of the paper？ HOT 1
- Clarification on how to interpret PET's results HOT 2
- A question about “Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification”
- RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)` HOT 3
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