Update cal_lr.py
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5619e76dc5
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@ -32,19 +32,14 @@ def calculate_lr(
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dataset=dataset,
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dataset=dataset,
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template="default",
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template="default",
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cutoff_len=cutoff_len,
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cutoff_len=cutoff_len,
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output_dir="dummy_dir",
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output_dir="dummy_dir"
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fp16=True
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))
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))
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trainset = get_dataset(model_args, data_args)
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trainset = get_dataset(model_args, data_args)
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_, tokenizer = load_model_and_tokenizer(model_args, finetuning_args, is_trainable=False, stage="sft")
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_, tokenizer = load_model_and_tokenizer(model_args, finetuning_args, is_trainable=False, stage="sft")
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trainset = preprocess_dataset(trainset, tokenizer, data_args, training_args, stage="sft")
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trainset = preprocess_dataset(trainset, tokenizer, data_args, training_args, stage="sft")
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data_collator = DataCollatorForSeq2Seq(tokenizer=tokenizer, label_pad_token_id=IGNORE_INDEX)
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data_collator = DataCollatorForSeq2Seq(tokenizer=tokenizer, label_pad_token_id=IGNORE_INDEX)
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dataloader = DataLoader(
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dataloader = DataLoader(
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dataset=trainset,
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dataset=trainset, batch_size=batch_size, shuffle=True, collate_fn=data_collator, pin_memory=True
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batch_size=batch_size,
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shuffle=True,
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collate_fn=data_collator,
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pin_memory=True
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)
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)
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valid_tokens, total_tokens = 0, 0
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valid_tokens, total_tokens = 0, 0
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for batch in tqdm(dataloader):
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for batch in tqdm(dataloader):
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