diff --git a/configs/training_config.yaml b/configs/training_config.yaml index d5302df..e0f5e81 100644 --- a/configs/training_config.yaml +++ b/configs/training_config.yaml @@ -26,7 +26,7 @@ training: save_total_limit: 3 # Evaluation - evaluation_strategy: "steps" + eval_strategy: "steps" eval_steps: 100 load_best_model_at_end: true metric_for_best_model: "loss" diff --git a/configs/training_config_qwen3.yaml b/configs/training_config_qwen3.yaml index dbfab51..9774994 100644 --- a/configs/training_config_qwen3.yaml +++ b/configs/training_config_qwen3.yaml @@ -26,7 +26,7 @@ training: save_total_limit: 3 # Evaluation - evaluation_strategy: "steps" + eval_strategy: "steps" eval_steps: 100 load_best_model_at_end: true metric_for_best_model: "loss" diff --git a/logs/events.out.tfevents.1755867795.Suherdy-Laptop.20720.0 b/logs/events.out.tfevents.1755867795.Suherdy-Laptop.20720.0 new file mode 100644 index 0000000..0c3ad3e Binary files /dev/null and b/logs/events.out.tfevents.1755867795.Suherdy-Laptop.20720.0 differ diff --git a/src/config.py b/src/config.py index dddcbdc..faf1da6 100644 --- a/src/config.py +++ b/src/config.py @@ -33,7 +33,7 @@ class TrainingConfig: logging_steps: int = 1 save_steps: int = 100 save_total_limit: int = 3 - evaluation_strategy: str = "steps" + eval_strategy: str = "steps" eval_steps: int = 100 load_best_model_at_end: bool = True metric_for_best_model: str = "loss" @@ -187,7 +187,7 @@ class AppConfig: 'logging_steps': self.training.logging_steps, 'save_steps': self.training.save_steps, 'save_total_limit': self.training.save_total_limit, - 'evaluation_strategy': self.training.evaluation_strategy, + 'eval_strategy': self.training.eval_strategy, 'eval_steps': self.training.eval_steps, 'load_best_model_at_end': self.training.load_best_model_at_end, 'metric_for_best_model': self.training.metric_for_best_model, diff --git a/src/trainer.py b/src/trainer.py index f9c6175..280c33a 100644 --- a/src/trainer.py +++ b/src/trainer.py @@ -189,7 +189,7 @@ class ModelTrainer: logging_steps=self.config.training.logging_steps, save_steps=self.config.training.save_steps, save_total_limit=self.config.training.save_total_limit, - evaluation_strategy=self.config.training.evaluation_strategy, + eval_strategy=self.config.training.eval_strategy, eval_steps=self.config.training.eval_steps, load_best_model_at_end=self.config.training.load_best_model_at_end, metric_for_best_model=self.config.training.metric_for_best_model,