e1698e05c7The post-filter safety net for 'Train on completions' fires when train_on_responses_only() masks every token in too many rows. Its trigger is a row-drop ratio, not a token-length check, but the message hardcoded "max_seq_length is too short, try increasing (e.g. 8192)" -- advice that fires identically at any max_seq_length and can recommend a value below the user's current setting (telling someone already at 16384 to use 8192). The dominant real cause is that the model's response template is not found in the formatted samples: the dataset is already formatted, or its structure doesn't match the model's chat template, so every token gets masked and the rows are dropped. Reword the error (and the comment above it) to lead with that cause and the actionable fix (turn off 'Train on completions'), and mention max_seq_length only as a secondary possibility without a hardcoded recommendation. |
||
|---|---|---|
| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||