Trying to fine tune with different data, But getting dimensionality mismatched for tensor

I am getting the following error while trying to fine tune

```
InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [326,64] rhs shape= [1427,64]
[[Node: save/Assign_746 = Assign[T=DT_FLOAT, _class=["loc:@char_mat"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](char_mat, save/RestoreV2:746)]]
```

Start with the save/Assign_746 restore node in the traceback and inspect the char_mat tensor shapes: [326,64] and [1427,64]. Determine why the fine-tuning data and restored checkpoint use different dimensions, then verify that checkpoint restoration completes with matching shapes.

Written by the indexing model from the issue text.