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from datasets import load_dataset |
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from transformers import FastSpeechForConditionalGeneration, Trainer, TrainingArguments |
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dataset = load_dataset("m6011/sada2022") |
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najdi_data = dataset.filter(lambda example: example['SpeakerDialect'] == 'Najdi') |
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model = FastSpeechForConditionalGeneration.from_pretrained("facebook/fastspeech2-en-ljspeech") |
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training_args = TrainingArguments( |
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output_dir="./results", |
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per_device_train_batch_size=4, |
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num_train_epochs=5, |
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) |
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trainer = Trainer( |
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model=model, |
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args=training_args, |
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train_dataset=najdi_data['train'], |
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eval_dataset=najdi_data['test'] |
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) |
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trainer.train() |
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