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fix: remove redundant configs from rebase mistake

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This commit is contained in:
NanoCode012
2025-05-15 16:07:37 +07:00
parent 555190868a
commit 64a57ebb62
2 changed files with 6 additions and 15 deletions
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5
src/axolotl/core/trainer_builder/base.py
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@@ -270,6 +270,11 @@ class TrainerBuilderBase(abc.ABC):
"dataloader_prefetch_factor",
"gradient_accumulation_steps",
"learning_rate",
"embedding_lr",
"embedding_lr_scale",
"lr_groups",
"loraplus_lr_ratio",
"loraplus_lr_embedding",
"output_dir",
"save_safetensors",
"save_only_model",

16
src/axolotl/core/trainer_builder/sft.py
View File

@@ -259,10 +259,6 @@ class HFCausalTrainerBuilder(TrainerBuilderBase):
training_arguments_kwargs["group_by_length"] = self.cfg.group_by_length
training_arguments_kwargs["curriculum_sampling"] = self.cfg.curriculum_sampling
training_arguments_kwargs["embedding_lr"] = self.cfg.embedding_lr
training_arguments_kwargs["embedding_lr_scale"] = self.cfg.embedding_lr_scale
training_arguments_kwargs["lr_groups"] = self.cfg.lr_groups
training_arguments_kwargs["sample_packing"] = bool(self.cfg.sample_packing)
training_arguments_kwargs["multipack_real_batches"] = (
not self.cfg.flash_attention or self.cfg.multipack_real_batches
@@ -322,17 +318,6 @@ class HFCausalTrainerBuilder(TrainerBuilderBase):
self.cfg.neftune_noise_alpha
)
trainer_kwargs = {}
training_arguments_kwargs["embedding_lr"] = self.cfg.embedding_lr
training_arguments_kwargs["embedding_lr_scale"] = self.cfg.embedding_lr_scale
training_arguments_kwargs["loraplus_lr_ratio"] = self.cfg.loraplus_lr_ratio
training_arguments_kwargs["loraplus_lr_embedding"] = (
self.cfg.loraplus_lr_embedding
)
training_arguments_kwargs["lr_groups"] = self.cfg.lr_groups
if self.cfg.accelerator_config:
training_arguments_kwargs["accelerator_config"] = (
self.cfg.accelerator_config
@@ -390,6 +375,7 @@ class HFCausalTrainerBuilder(TrainerBuilderBase):
data_collator_kwargs["pad_to_multiple_of"] = multiple
trainer_cls = self._get_trainer_cls()
trainer_kwargs = {}
trainer_kwargs, trainer_cls = self.hook_pre_create_trainer(
trainer_kwargs, trainer_cls
)