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Commit 271d1c9e authored by Мазур Грета Евгеньевна's avatar Мазур Грета Евгеньевна
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supermega

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with 12 additions and 12 deletions
+12 -12
.ipynb_checkpoints/ULTRAMegaOB-checkpoint.py
+ 6
− 6
View file @ 271d1c9e
...@@ -141,10 +141,10 @@ def compute_metrics(p): ...@@ -141,10 +141,10 @@ def compute_metrics(p):
"support": attack_report[attack_type]["support"] "support": attack_report[attack_type]["support"]
} }
metrics = { metrics = {
'accuracy': safety_report["accuracy"], 'eval_accuracy': safety_report["accuracy"],
'f1': safety_report["weighted avg"]["f1-score"], 'eval_f1': safety_report["weighted avg"]["f1-score"],
'unsafe_recall': safety_report["unsafe"]["recall"], # Без eval_ префикса 'eval_unsafe_recall': safety_report["unsafe"]["recall"], # Добавляем eval_ префикс
'safe_precision': safety_report["safe"]["precision"], 'eval_safe_precision': safety_report["safe"]["precision"],
} }
# Добавляем метрики для атак (только если есть unsafe примеры) # Добавляем метрики для атак (только если есть unsafe примеры)
...@@ -553,7 +553,7 @@ def train_model(): ...@@ -553,7 +553,7 @@ def train_model():
logging_steps=100, logging_steps=100,
save_total_limit=2, save_total_limit=2,
# load_best_model_at_end=True, # load_best_model_at_end=True,
metric_for_best_model="unsafe_recall", # metric_for_best_model="unsafe_recall",
# greater_is_better=True, # greater_is_better=True,
fp16=True, # Принудительное использование mixed precision fp16=True, # Принудительное использование mixed precision
fp16_full_eval=True, fp16_full_eval=True,
...@@ -561,7 +561,7 @@ def train_model(): ...@@ -561,7 +561,7 @@ def train_model():
report_to="none", report_to="none",
seed=Config.SEED, seed=Config.SEED,
max_grad_norm=1.0, max_grad_norm=1.0,
# metric_for_best_model="eval_unsafe_recall", metric_for_best_model="eval_unsafe_recall",
greater_is_better=True, greater_is_better=True,
load_best_model_at_end=True, load_best_model_at_end=True,
) )
......
ULTRAMegaOB.py
+ 6
− 6
View file @ 271d1c9e
...@@ -141,10 +141,10 @@ def compute_metrics(p): ...@@ -141,10 +141,10 @@ def compute_metrics(p):
"support": attack_report[attack_type]["support"] "support": attack_report[attack_type]["support"]
} }
metrics = { metrics = {
'accuracy': safety_report["accuracy"], 'eval_accuracy': safety_report["accuracy"],
'f1': safety_report["weighted avg"]["f1-score"], 'eval_f1': safety_report["weighted avg"]["f1-score"],
'unsafe_recall': safety_report["unsafe"]["recall"], # Без eval_ префикса 'eval_unsafe_recall': safety_report["unsafe"]["recall"], # Добавляем eval_ префикс
'safe_precision': safety_report["safe"]["precision"], 'eval_safe_precision': safety_report["safe"]["precision"],
} }
# Добавляем метрики для атак (только если есть unsafe примеры) # Добавляем метрики для атак (только если есть unsafe примеры)
...@@ -553,7 +553,7 @@ def train_model(): ...@@ -553,7 +553,7 @@ def train_model():
logging_steps=100, logging_steps=100,
save_total_limit=2, save_total_limit=2,
# load_best_model_at_end=True, # load_best_model_at_end=True,
metric_for_best_model="unsafe_recall", # metric_for_best_model="unsafe_recall",
# greater_is_better=True, # greater_is_better=True,
fp16=True, # Принудительное использование mixed precision fp16=True, # Принудительное использование mixed precision
fp16_full_eval=True, fp16_full_eval=True,
...@@ -561,7 +561,7 @@ def train_model(): ...@@ -561,7 +561,7 @@ def train_model():
report_to="none", report_to="none",
seed=Config.SEED, seed=Config.SEED,
max_grad_norm=1.0, max_grad_norm=1.0,
# metric_for_best_model="eval_unsafe_recall", metric_for_best_model="eval_unsafe_recall",
greater_is_better=True, greater_is_better=True,
load_best_model_at_end=True, load_best_model_at_end=True,
) )
......
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