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fix args

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Former-commit-id: 44d0fa2ac6a6423c7ddaf91eb8998c1b9248c04e
This commit is contained in:
hiyouga 2023-11-07 16:36:06 +08:00
parent 2084133058
commit 857696ed9c
4 changed files with 8 additions and 8 deletions
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4
src/llmtuner/tuner/dpo/workflow.py
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@ -60,9 +60,9 @@ def run_dpo(
plot_loss(training_args.output_dir, keys=["loss", "eval_loss"])
if training_args.push_to_hub:
trainer.push_to_hub(**generate_model_card())
trainer.push_to_hub(**generate_model_card(model_args, data_args, finetuning_args))
else:
trainer.create_model_card(**generate_model_card())
trainer.create_model_card(**generate_model_card(model_args, data_args, finetuning_args))
# Evaluation
if training_args.do_eval:

4
src/llmtuner/tuner/pt/workflow.py
View File

@ -46,9 +46,9 @@ def run_pt(
plot_loss(training_args.output_dir, keys=["loss", "eval_loss"])
if training_args.push_to_hub:
trainer.push_to_hub(**generate_model_card())
trainer.push_to_hub(**generate_model_card(model_args, data_args, finetuning_args))
else:
trainer.create_model_card(**generate_model_card())
trainer.create_model_card(**generate_model_card(model_args, data_args, finetuning_args))
# Evaluation
if training_args.do_eval:

4
src/llmtuner/tuner/rm/workflow.py
View File

@ -54,9 +54,9 @@ def run_rm(
plot_loss(training_args.output_dir, keys=["loss", "eval_loss"])
if training_args.push_to_hub:
trainer.push_to_hub(**generate_model_card())
trainer.push_to_hub(**generate_model_card(model_args, data_args, finetuning_args))
else:
trainer.create_model_card(**generate_model_card())
trainer.create_model_card(**generate_model_card(model_args, data_args, finetuning_args))
# Evaluation
if training_args.do_eval:

4
src/llmtuner/tuner/sft/workflow.py
View File

@ -73,9 +73,9 @@ def run_sft(
plot_loss(training_args.output_dir, keys=["loss", "eval_loss"])
if training_args.push_to_hub:
trainer.push_to_hub(**generate_model_card())
trainer.push_to_hub(**generate_model_card(model_args, data_args, finetuning_args))
else:
trainer.create_model_card(**generate_model_card())
trainer.create_model_card(**generate_model_card(model_args, data_args, finetuning_args))
# Evaluation
if training_args.do_eval: