training about ditto HOT 7 OPEN

I see. I tried the CPU version and got the same error. It seems to be related to data augmentation but I am not sure. I tried the baseline version (no DA) and it works fine on CPU:

CUDA_VISIBLE_DEVICES= python train_ditto.py   --task Structured/Beer   --batch_size 32   --max_len 128   --lr 3e-5   --n_epochs 40   --finetuning   --lm distilbert

You might also use this colab notebook to run it on GPUs.

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I see. Will fix the bug of infinite loops. The hyper-parameters are not ideal for this dataset either (I will change the README with an updated set). Meanwhile, you can try this one

CUDA_VISIBLE_DEVICES=0 python train_ditto.py \
  --task Structured/Beer \
  --batch_size 32 \
  --max_len 128 \
  --lr 3e-5 \
  --n_epochs 40 \
  --finetuning \
  --lm roberta \
  --fp16 \
  --da drop_col

which should work better.

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I have this same error before as well, forgot to capture this

/data/home/vijaya.chennupati/.conda/envs/txtclass/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1221: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples. Use zero_division parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
accuracy=0.846
precision=0.000
recall=0.000
f1=0.000

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I am using CPU ... so removed the parameter --fp16 , no luck runs into infinite loop

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Will give it a try.

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Hello, does the latest version fixed this bug?
I also have this problem when I use CPU to train my program...

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