为何满足EarlyStoppingCallback条件时Seq2SeqTrainer未停止训练？

尝试给Seq2SeqTrainer配置EarlyStoppingCallback，设置patience=2、threshold=1.0，代码如下：

training_args = Seq2SeqTrainingArguments(
    output_dir='./',
    num_train_epochs=3,
    per_device_train_batch_size=4,
    per_device_eval_batch_size=4,
    logging_steps=1,
    save_steps=5,
    eval_steps=1,
    max_steps=10,
    evaluation_strategy="steps",
    predict_with_generate=True,
    report_to=None,
    metric_for_best_model="chr_f_score",
    load_best_model_at_end=True
)

early_stop = EarlyStoppingCallback(2, 1.0)

trainer = Seq2SeqTrainer(
    model=model,
    args=training_args,
    train_dataset=valid_data.with_format("torch"),
    eval_dataset=test_data.with_format("torch"),
    compute_metrics=compute_metrics,
    callbacks=[early_stop]
)

trainer.train()

实际训练时，模型并未在满足早停条件后终止，而是持续训练直到达到max_steps的上限。

核心疑问 #

为何满足EarlyStoppingCallback的触发条件时，Seq2SeqTrainer没有停止训练？

训练结束后检查发现，早停计数器已经达到阈值，但训练并未提前终止：

>>> early_stop.early_stopping_patience_counter
2

内容的提问来源于stack exchange，提问作者alvas