* Validation split percentage to be used for custom data files also Issue same as https://github.com/huggingface/transformers/issues/12406 fixed for pytorch branch run_mlm.py * Validation split added in the right place * Update run_clm.py * validation split added for custom files * Validation split added for custom files * Update run_plm.py * fixed validation split for custom files as input for pytorch examples in lm * Update run_clm_no_trainer.py * args modified
This commit is contained in:
committed by
GitHub
parent
3488ef5a92
commit
1d6623c6a2
@@ -278,6 +278,21 @@ def main():
|
||||
if extension == "txt":
|
||||
extension = "text"
|
||||
raw_datasets = load_dataset(extension, data_files=data_files, cache_dir=model_args.cache_dir)
|
||||
# If no validation data is there, validation_split_percentage will be used to divide the dataset.
|
||||
if "validation" not in raw_datasets.keys():
|
||||
raw_datasets["validation"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[:{data_args.validation_split_percentage}%]",
|
||||
cache_dir=model_args.cache_dir,
|
||||
)
|
||||
raw_datasets["train"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[{data_args.validation_split_percentage}%:]",
|
||||
cache_dir=model_args.cache_dir,
|
||||
)
|
||||
|
||||
# See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at
|
||||
# https://huggingface.co/docs/datasets/loading_datasets.html.
|
||||
|
||||
|
||||
@@ -253,6 +253,19 @@ def main():
|
||||
if extension == "txt":
|
||||
extension = "text"
|
||||
raw_datasets = load_dataset(extension, data_files=data_files)
|
||||
# If no validation data is there, validation_split_percentage will be used to divide the dataset.
|
||||
if "validation" not in raw_datasets.keys():
|
||||
raw_datasets["validation"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[:{args.validation_split_percentage}%]",
|
||||
)
|
||||
raw_datasets["train"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[{args.validation_split_percentage}%:]",
|
||||
)
|
||||
|
||||
# See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at
|
||||
# https://huggingface.co/docs/datasets/loading_datasets.html.
|
||||
|
||||
|
||||
@@ -285,6 +285,22 @@ def main():
|
||||
if extension == "txt":
|
||||
extension = "text"
|
||||
raw_datasets = load_dataset(extension, data_files=data_files, cache_dir=model_args.cache_dir)
|
||||
|
||||
# If no validation data is there, validation_split_percentage will be used to divide the dataset.
|
||||
if "validation" not in raw_datasets.keys():
|
||||
raw_datasets["validation"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[:{data_args.validation_split_percentage}%]",
|
||||
cache_dir=model_args.cache_dir,
|
||||
)
|
||||
raw_datasets["train"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[{data_args.validation_split_percentage}%:]",
|
||||
cache_dir=model_args.cache_dir,
|
||||
)
|
||||
|
||||
# See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at
|
||||
# https://huggingface.co/docs/datasets/loading_datasets.html.
|
||||
|
||||
|
||||
@@ -265,6 +265,19 @@ def main():
|
||||
if extension == "txt":
|
||||
extension = "text"
|
||||
raw_datasets = load_dataset(extension, data_files=data_files)
|
||||
# If no validation data is there, validation_split_percentage will be used to divide the dataset.
|
||||
if "validation" not in raw_datasets.keys():
|
||||
raw_datasets["validation"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[:{args.validation_split_percentage}%]",
|
||||
)
|
||||
raw_datasets["train"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[{args.validation_split_percentage}%:]",
|
||||
)
|
||||
|
||||
# See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at
|
||||
# https://huggingface.co/docs/datasets/loading_datasets.html.
|
||||
|
||||
|
||||
@@ -280,6 +280,21 @@ def main():
|
||||
if extension == "txt":
|
||||
extension = "text"
|
||||
raw_datasets = load_dataset(extension, data_files=data_files, cache_dir=model_args.cache_dir)
|
||||
# If no validation data is there, validation_split_percentage will be used to divide the dataset.
|
||||
if "validation" not in raw_datasets.keys():
|
||||
raw_datasets["validation"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[:{data_args.validation_split_percentage}%]",
|
||||
cache_dir=model_args.cache_dir,
|
||||
)
|
||||
raw_datasets["train"] = load_dataset(
|
||||
extension,
|
||||
data_files=data_files,
|
||||
split=f"train[{data_args.validation_split_percentage}%:]",
|
||||
cache_dir=model_args.cache_dir,
|
||||
)
|
||||
|
||||
# See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at
|
||||
# https://huggingface.co/docs/datasets/loading_datasets.html.
|
||||
|
||||
|
||||
Reference in New Issue
Block a user