243620394a
* fix: force train split for json,csv,txt for test_datasets * feat(doc): add info on mixing datasets for VLM * feat(doc): max memory * fix(doc): clarify lr groups * fix: add info on vision not being dropped * feat: add qwen3-vl to multimodal docs * fix: add moe blocks to arch list * feat(doc): improve mistral docs * chore: add helpful link [skip-e2e] * fix: add vram usage for mistral small * Update link in docs/faq.qmd Co-authored-by: salman <salman.mohammadi@outlook.com> --------- Co-authored-by: Wing Lian <wing@axolotl.ai> Co-authored-by: salman <salman.mohammadi@outlook.com>
36 lines
1.0 KiB
Plaintext
36 lines
1.0 KiB
Plaintext
---
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title: Learning Rate Groups
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description: "Setting different learning rates by module name"
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---
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## Background
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Inspired by LoRA+, Axolotl allows practitioners to specify separate learning rates for each module or groups of
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modules in a model.
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## Example
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```yaml
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lr_groups:
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- name: o_proj
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modules:
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- self_attn.o_proj.weight
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lr: 1e-6
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- name: q_proj
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modules:
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- model.layers.2.self_attn.q_proj.weight
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lr: 1e-5
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learning_rate: 2e-5
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```
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In this example, we have a default learning rate of 2e-5 across the entire model, but we have a separate learning rate
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of 1e-6 for all the self attention `o_proj` modules across all layers, and a learning are of 1e-5 to the 3rd layer's
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self attention `q_proj` module.
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::: {.callout-note}
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We currently only support varying `lr` for now. If you're interested in adding support for others (`weight_decay`), we welcome PRs. See https://github.com/axolotl-ai-cloud/axolotl/blob/613bcf90e58f3ab81d3827e7fc572319908db9fb/src/axolotl/core/trainers/mixins/optimizer.py#L17
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:::
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