# Seq2SeqTrainer, \`push\_to\_hub\` returns None
**URL:**
**Author:**  [@auhide](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fauhide)%5C
**Post date:** [April 17, 2023, 9:15pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fseq2seqtrainer-push-to-hub-returns-none%2F36887%2F1 "2023-04-17T21:15:39Z")
Hi,
When I try to fine-tune the `m5-small` model with `Seq2SeqTrainer` I get this error:
```bash
3550 commit_message = f"Training in progress, epoch {int(self.state.epoch)}"
3551 _, self.push_in_progress = self.repo.push_to_hub(
-> 3552 commit_message=commit_message, blocking=False, auto_lfs_prune=True
3553 )
3554 finally:
TypeError: cannot unpack non-iterable NoneType object
```
Here is my code. I’ll start with the model & tokenizer initialization:
```python
MODEL_ID = "google/mt5-small"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID)
```
And here are the `Seq2SeqTrainingArguments` and `Seq2SeqTrainer`:
```python
MODEL_NAME = "mt5-bg-small"
EPOCHS = 15
L_RATE = 2e-4
W_DECAY = 0.01
TRAIN_BATCH_SIZE = 4
EVAL_BATCH_SIZE = 4
training_args = Seq2SeqTrainingArguments(
output_dir=MODEL_NAME,
evaluation_strategy="epoch",
learning_rate=L_RATE,
per_device_train_batch_size=TRAIN_BATCH_SIZE,
per_device_eval_batch_size=EVAL_BATCH_SIZE,
weight_decay=W_DECAY,
save_total_limit=1,
num_train_epochs=EPOCHS,
# predict_with_generate=True,
fp16=True,
push_to_hub=True,
report_to="none",
# Not calculating the additional metrics - only the loss.
prediction_loss_only=True
)
trainer = Seq2SeqTrainer(
model=model,
args=training_args,
train_dataset=train_dataset,
eval_dataset=eval_dataset,
tokenizer=tokenizer,
data_collator=data_collator,
)
trainer.train()
tokenizer.push_to_hub(MODEL_NAME)
```
The error occurs at the 2^{nd} saving step (in my case 1000^{th} step)
I am successfully logged into my account, using a WRITE Access Token. What might be the problem?
_Please note - I am using a Kaggle Notebook with a GPU._
Thank you in advance,
Adam
---
**Author:**  [@zoebat20](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fzoebat20)%5C
**Post date:** [May 10, 2023, 9:37am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fseq2seqtrainer-push-to-hub-returns-none%2F36887%2F2 "2023-05-10T09:37:42Z")
Hi @auhide ,
Were you able to figure out what the problem was? I am having the exact same issue when fine-tuning a GPT-J model.
---
**Author:**  [@auhide](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fauhide)%5C
**Post date:** [May 10, 2023, 1:40pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fseq2seqtrainer-push-to-hub-returns-none%2F36887%2F3 "2023-05-10T13:40:17Z")
Hi @zoebat20,
I was not able to figure out what the problem was. I tried different things though.
Changing the base model helped. In my case, instead of using the `google/mt5-small` model (1.2 GB), I used `t5-small` or `t5-base` (242 MB and 898 MB respectively).
I guess the problem was the model size? Not sure why though.