dfba881e99
* feat: add gemma3n cce
* feat: add sample config
* feat: add gemma3n multimodal mode
* feat: add audio example
* feat: support audio and return pixel values in collator
* feat: support unmask only assistant region (gemma3n for now)
* feat(doc): add notes for audio loading
* feat: add audio support for gemma3n
* feat: update examples
* feat: add gemma3n to the docs
* fix: add link at top
* feat(doc): clarify additional requirements
* fix: mllama missing aspect ratio
* fix: mllama need attention fixes for fa2
* Partially Revert "fix: mllama need attention fixes for fa2"
This reverts commit a0bfdd1777.
* fix: disable FA2 for mllama in vision mode
* feat: update configs to use proper attention
* fix: support other vision features
* feat(doc): clarify requirements for gemma3n
76 lines
1.6 KiB
YAML
76 lines
1.6 KiB
YAML
base_model: google/gemma-3n-E2B-it
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processor_type: AutoProcessor
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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plugins:
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
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cut_cross_entropy: true
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# for use with fft to only train on language model layers
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# unfrozen_parameters:
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# - model.language_model.*
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# - lm_head
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# - embed_tokens
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load_in_4bit: true
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# these 3 lines are needed for now to handle vision chat templates w images
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skip_prepare_dataset: true
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remove_unused_columns: false
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sample_packing: false
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# gemma3 doesn't seem to play nice with ddp
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ddp_find_unused_parameters: true
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chat_template: gemma3n
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eot_tokens:
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- <end_of_turn>
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datasets:
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- path: HuggingFaceH4/llava-instruct-mix-vsft
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type: chat_template
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split: train[:1%]
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dataset_prepared_path:
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val_set_size: 0.01
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output_dir: ./outputs/out
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adapter: qlora
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lora_model_dir:
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sequence_len: 2048
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pad_to_sequence_len: false
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_modules: 'model.language_model.layers.[\d]+.(mlp|self_attn).(up|down|gate|q|k|v|o)_proj'
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 1
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optimizer: muon
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lr_scheduler: cosine
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learning_rate: 0.0002
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bf16: true
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fp16:
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tf32: true
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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logging_steps: 1
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# flash_attention: true # Any attention impl does not work with gemma3n now
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warmup_ratio: 0.1
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evals_per_epoch: 1
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saves_per_epoch: 1
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weight_decay: 0.0
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