Comments (1)
Niklss
commented on September 26, 2024
How much GPU memory is required for model training? If the GPU memory is not enough, how can model parameters be optimized (batch_size has been set to 1)?
I've been able to start training t5_large based ere model with flant5_large_conll04 config (except use_amp, I changed it to false. V100 is not working with bf16). It requires 25870MiB of GPU memory.
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Related Issues (17)
- Missing 'conll03_to_json.py' HOT 1
- pyhocon: Cannot resolve variable ${t5_3b_ace05_wu08}
- Missing test evaluation HOT 2
- Upload the finetuned model please HOT 2
- How can I make prediction from a text file HOT 5
- RuntimeError: Device index must not be negative HOT 1
- How to understand the predicted relations
- Issue in running the evaluation for ERE as per README.md HOT 1
- coref HOT 3
- Model inputs HOT 4
- run_ner.py error：Is this error related to the path of Pretrained LM? HOT 2
- Pretrained Models HOT 6
- Issue with installing Apex. Any option to run code without it? HOT 3
- About entity's right boundary in ERE HOT 1
- Missing entities on data preparation with conll03_to_json.py
- missing requirements.txt
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