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🚨🚨🚨Deprecate evaluation_strategy to eval_strategy🚨🚨🚨 (#30190)

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This commit is contained in:
Zach Mueller
2024-04-18 12:49:43 -04:00
committed by GitHub
parent c86d020ead
commit 60d5f8f9f0
116 changed files with 214 additions and 203 deletions
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10
examples/research_projects/self-training-text-classification/finetuning.py
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@@ -190,7 +190,7 @@ class FTTrainingArguments:
)
},
)
evaluation_strategy: Optional[str] = dataclasses.field(
eval_strategy: Optional[str] = dataclasses.field(
default="no",
metadata={
"help": 'The evaluation strategy to adopt during training. Possible values are: ["no", "step", "epoch]'
@@ -198,7 +198,7 @@ class FTTrainingArguments:
)
eval_steps: Optional[int] = dataclasses.field(
default=1,
metadata={"help": 'Number of update steps between two evaluations if `evaluation_strategy="steps"`.'},
metadata={"help": 'Number of update steps between two evaluations if `eval_strategy="steps"`.'},
)
eval_metric: Optional[str] = dataclasses.field(
default="accuracy", metadata={"help": "The evaluation metric used for the task."}
@@ -265,7 +265,7 @@ def train(args, accelerator, model, tokenizer, train_dataloader, optimizer, lr_s
# Evaluate during training
if (
eval_dataloader is not None
and args.evaluation_strategy == IntervalStrategy.STEPS.value
and args.eval_strategy == IntervalStrategy.STEPS.value
and args.eval_steps > 0
and completed_steps % args.eval_steps == 0
):
@@ -331,7 +331,7 @@ def train(args, accelerator, model, tokenizer, train_dataloader, optimizer, lr_s
break
# Evaluate during training
if eval_dataloader is not None and args.evaluation_strategy == IntervalStrategy.EPOCH.value:
if eval_dataloader is not None and args.eval_strategy == IntervalStrategy.EPOCH.value:
accelerator.wait_for_everyone()
new_checkpoint = f"checkpoint-{IntervalStrategy.EPOCH.value}-{epoch}"
new_eval_result = evaluate(args, accelerator, eval_dataloader, "eval", model, new_checkpoint)[
@@ -571,7 +571,7 @@ def finetune(accelerator, model_name_or_path, train_file, output_dir, **kwargs):
assert args.train_file is not None
data_files[Split.TRAIN.value] = args.train_file
if args.do_eval or args.evaluation_strategy != IntervalStrategy.NO.value:
if args.do_eval or args.eval_strategy != IntervalStrategy.NO.value:
assert args.eval_file is not None
data_files[Split.EVAL.value] = args.eval_file