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mod gemma

This commit is contained in:
l.gabrysiak 2025-02-26 13:56:35 +01:00
parent b0525e303d
commit b9d7a7adc5
1 changed files with 3 additions and 3 deletions
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6
gemma.py
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@ -65,7 +65,7 @@ lora_config = LoraConfig(
model = get_peft_model(model, lora_config) model = get_peft_model(model, lora_config)
# 7️⃣ Tokenizacja danych # 7️⃣ Tokenizacja danych
max_length = 128 max_length = 1024
def tokenize_function(examples): def tokenize_function(examples):
return tokenizer( return tokenizer(
@ -85,10 +85,10 @@ training_args = TrainingArguments(
eval_steps=500, # Ewaluacja co 500 kroków eval_steps=500, # Ewaluacja co 500 kroków
save_strategy="steps", # Zapis modelu co określoną liczbę kroków save_strategy="steps", # Zapis modelu co określoną liczbę kroków
save_steps=500, # Zapis modelu co 500 kroków save_steps=500, # Zapis modelu co 500 kroków
learning_rate=2e-5, learning_rate=1e-5,
per_device_train_batch_size=2, per_device_train_batch_size=2,
per_device_eval_batch_size=2, per_device_eval_batch_size=2,
num_train_epochs=5, num_train_epochs=32,
weight_decay=0.01, weight_decay=0.01,
load_best_model_at_end=True, # Wczytaj najlepszy model na końcu load_best_model_at_end=True, # Wczytaj najlepszy model na końcu
metric_for_best_model="loss", # Kryterium wyboru najlepszego modelu metric_for_best_model="loss", # Kryterium wyboru najlepszego modelu