4f65cc94bcAdd per-model YAML configs and MODEL_NAME_MAPPING entries for all 8 Gemma 4 models (4 instruct + 4 base): - gemma-4-31B-it / gemma-4-31B - gemma-4-26B-A4B-it / gemma-4-26B-A4B - gemma-4-E2B-it / gemma-4-E2B - gemma-4-E4B-it / gemma-4-E4B GGUF variants (only for -it models) resolve via the gemma-4 family entry in inference_defaults.json. Sampling defaults: temperature=1.0, top_p=0.95, top_k=64, min_p=0.0, no repetition or presence penalty. Matches gemma-3n and gemma-3.
47 lines
968 B
YAML
47 lines
968 B
YAML
# Model defaults for unsloth/gemma-4-31B (base/pretrained)
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# Also applies to: google/gemma-4-31B
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training:
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trust_remote_code: false
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max_seq_length: 2048
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num_epochs: 0
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learning_rate: 2e-4
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batch_size: 2
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gradient_accumulation_steps: 4
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warmup_steps: 5
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max_steps: 30
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save_steps: 30
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weight_decay: 0.001
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random_seed: 3407
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packing: false
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train_on_completions: true
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gradient_checkpointing: "unsloth"
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optim: "adamw_8bit"
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lr_scheduler_type: "linear"
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lora:
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lora_r: 8
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lora_alpha: 8
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lora_dropout: 0.0
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target_modules:
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- "all-linear"
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use_rslora: false
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use_loftq: false
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finetune_vision_layers: true
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finetune_language_layers: true
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finetune_attention_modules: true
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finetune_mlp_modules: true
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logging:
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enable_wandb: false
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wandb_project: "llm-finetuning"
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enable_tensorboard: false
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tensorboard_dir: "runs"
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log_frequency: 10
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inference:
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trust_remote_code: false
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temperature: 1.0
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top_p: 0.95
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top_k: 64
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min_p: 0.0
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