Hi all, I’m training a binary text classification model. In order to debug, I’m training and evaluating on a small subset of the data (around 16 data points) to see if the model can successfully overfit. However, the train_loss logged to Weights and Biases are not showing correctly – as you can see from the screenshot, it’s just a single point. Any idea on why this happened?
Below are my training code:
model = AutoModelForSequenceClassification.from_pretrained("roberta-large")
training_args = TrainingArguments(
output_dir='./results',
learning_rate=1e-3,
per_device_train_batch_size=4,
per_device_eval_batch_size=4,
num_train_epochs=5,
evaluation_strategy="epoch",
logging_steps=1,
# weight_decay=0.01,
)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=encoded_ds,
eval_dataset=encoded_ds,
tokenizer=tokenizer,
compute_metrics=compute_metrics,
# data_collator=data_collator,
)