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---
title: vessl.progress
version: EN
---
# vessl.progress
Use `vessl.progress` to track the progress of your experiment. VESSL provides an estimate of a remaining training time by calculating the average elapsed time of previous epochs or batch sizes. You can view this information by hovering over the status of a running experiment. This can be used in both VESSL's managed server or in a local environment. 
| Parameter | Description |
| --------- | -------------------------------------------------- |
| `value` | Amount of progress (decimal value between 0 and 1) |
### Examples
```python
import vessl
for epoch in range(epochs):
...
# Update experiment progress every epoch
vessl.progress((epoch+1) / epochs)
```
```python
def train(model, device, train_loader, optimizer, epoch, start_epoch):
model.train()
loss = 0
for batch_idx, (data, label) in enumerate(train_loader):
...
# Update experiment progress every batch
vessl.progress(
((epoch+1)*batch_size + batch_idx) / (batch_size * epochs))
)
```
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