checkpoint = "google/mt5-small" tokenizer = MT5Tokenizer.from_pretrained(checkpoint, legacy=False) model = MT5ForConditionalGeneration.from_pretarined(checkpoint)

Training

Epochs: 200
Optimizer: AdamW
Learning Rate: 2e-5
Weight decay: 0.01
Warm-ups: 0.05*total_steps
Scheduler: cosine

Downloads last month: 10

Safetensors

Model size

0.3B params

Tensor type

F32

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