File size: 870 Bytes
5fa1a76 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 |
training_args = TrainingArguments( output_dir="my_awesome_eli5_clm-model", evaluation_strategy="epoch", learning_rate=2e-5, weight_decay=0.01, push_to_hub=True, ) trainer = Trainer( model=model, args=training_args, train_dataset=lm_dataset["train"], eval_dataset=lm_dataset["test"], data_collator=data_collator, ) trainer.train() Once training is completed, use the [~transformers.Trainer.evaluate] method to evaluate your model and get its perplexity: import math eval_results = trainer.evaluate() print(f"Perplexity: {math.exp(eval_results['eval_loss']):.2f}") Perplexity: 49.61 Then share your model to the Hub with the [~transformers.Trainer.push_to_hub] method so everyone can use your model: trainer.push_to_hub() If you aren't familiar with finetuning a model with Keras, take a look at the basic tutorial! |