fine tunning
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@@ -145,7 +145,7 @@ training_args = TrainingArguments(
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per_device_train_batch_size=1,
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gradient_accumulation_steps=16,
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learning_rate=1e-4,
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num_train_epochs=3,
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num_train_epochs=2,
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max_steps=1000,
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fp16=False, # ⚠ disable AMP
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@@ -8,7 +8,7 @@ from nltk.translate.bleu_score import corpus_bleu
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# Configuration
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# ----------------------------
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BASE_MODEL = "Qwen/Qwen2.5-7B-Instruct" # base model
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LORA_DIR = "./qwen2.5-7b-uk-fr-lora" # fine-tuned LoRA
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LORA_DIR = "./qwen2.5-7b-uk-fr-lora-2epoch" # fine-tuned LoRA
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VALIDATION_FILE = "validation.jsonl" # small validation subset
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MAX_INPUT_LENGTH = 1024
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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