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@@ -348,11 +348,11 @@ The command below shows an example at an specific learning rate,
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  but you could try with other hyperparameters to obtain the best training and evaluation losses.
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  ```
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- python 5.run_clm-post.py --tokenizer_name /path/to/ZymCTRL
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  --do_train --do_eval --output_dir output --evaluation_strategy steps --eval_steps 10
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  --logging_steps 5 --save_steps 500 --num_train_epochs 28 --per_device_train_batch_size 1
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  --per_device_eval_batch_size 4 --cache_dir '.' --save_total_limit 2 --learning_rate 0.8e-04
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- --dataloader_drop_last True --model_name_or_path /path/to/ZymCTRL
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  ```
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  In any case, the original HuggingFace script run_clm.py can be found here:
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  https://github.com/huggingface/transformers/blob/master/examples/pytorch/language-modeling/run_clm.py
 
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  but you could try with other hyperparameters to obtain the best training and evaluation losses.
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  ```
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+ python 5.run_clm-post.py --tokenizer_name AI4PD/ZymCTRL
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  --do_train --do_eval --output_dir output --evaluation_strategy steps --eval_steps 10
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  --logging_steps 5 --save_steps 500 --num_train_epochs 28 --per_device_train_batch_size 1
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  --per_device_eval_batch_size 4 --cache_dir '.' --save_total_limit 2 --learning_rate 0.8e-04
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+ --dataloader_drop_last True --model_name_or_path AI4PD/ZymCTRL
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  ```
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  In any case, the original HuggingFace script run_clm.py can be found here:
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  https://github.com/huggingface/transformers/blob/master/examples/pytorch/language-modeling/run_clm.py