# How to use Adaptive Learning rate during training?
**URL:**
**Author:**  [@anzaman](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fanzaman)%5C
**Post date:** [August 10, 2021, 6:02pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-adaptive-learning-rate-during-training%2F9143%2F1 "2021-08-10T18:02:04Z")
Hi,
I am trying to train a Siamese network and want to incorporate adaptive learning rate during training.
So I have a SiameseTrainer which is a subclass of Trainer class. My question is am I doing something wrong that I get the error
```auto
TypeError: Object of type Tensor is not JSON serializable
```
in this line of my code:
```auto
train_result = trainer.train(resume_from_checkpoint=checkpoint)
```
My code runs for few epochs and then crashes. So what I am doing is below:
```auto
def compute_metrics(p: EvalPrediction):
correct_predictions = p.predictions[1] if isinstance(p.predictions, tuple) else p.predictions
labels = p.label_ids
return {
"MSE": np.mean((correct_predictions-labels)**2)
}
optimizer = Adafactor(
model.parameters(),
scale_parameter=True, # If True, learning rate is scaled by root mean square
)
lr_scheduler = AdafactorSchedule(optimizer)
trainer = SiameseTrainer(
model=model,
args=training_args,
train_dataset=train_dataset,
eval_dataset=eval_dataset,
data_collator=data_collator,
compute_metrics=compute_metrics,
tokenizer=tokenizer,
callbacks=[EarlyStoppingCallback(early_stopping_patience=2)],
optimizers=(optimizer, lr_scheduler)
)
```
When I comment out the **optimizers=(optimizer, lr\_scheduler)** parameter and run the code, it does not crash in the middle of epochs.
Appreciate any help!
---
**Author:**  [@poom-sci](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fpoom-sci)%5C
**Post date:** [November 5, 2021, 9:45am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-adaptive-learning-rate-during-training%2F9143%2F2 "2021-11-05T09:45:35Z")
Hi, anzaman
I am stuck on the same problem as you do. Have You fixed this one yet?
This is mine error.
##########UPDATE
I found a way to trick it by adding logging\_steps=9999999 in the trainer argument to make it not log between training , but is there any better solutions for this one.
---
**Author:**  [@enpassant](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fenpassant)%5C
**Post date:** [February 11, 2022, 5:11pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-adaptive-learning-rate-during-training%2F9143%2F3 "2022-02-11T17:11:57Z")
your trick worked for me too. do you know if there are any updates that allow using adaFactor in training and successfully log without tripping `TypeError: Object of type Tensor is not JSON serializable`
---
**Author:**  [@mmalandro](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fmmalandro)%5C
**Post date:** [August 20, 2022, 7:27pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-adaptive-learning-rate-during-training%2F9143%2F4 "2022-08-20T19:27:41Z")
I have the same problem.
---
**Author:**  [@jxm](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fjxm)%5C
**Post date:** [June 2, 2023, 2:41pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-adaptive-learning-rate-during-training%2F9143%2F5 "2023-06-02T14:41:19Z")
I ran into an issue like this when I inadvertently logged a metric in the trainer that was a Tensor instead of just a float. I did something like `average_scores.mean()`, which returned a Tensor object, which was somehow affixed to `Trainer.state` and then broke json-saving. I changed the metric computation to `average_scores.mean().item()` and this fixed the issue.