55 lines
1023 B
YAML
55 lines
1023 B
YAML
base_model: Qwen/Qwen1.5-MoE-A2.7B
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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trust_remote_code: true
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# Keep VRAM low
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load_in_8bit: false
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load_in_4bit: true
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datasets:
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- path: mhenrichsen/alpaca_2k_test
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.05
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output_dir: ./outputs/qwen2-moe-qlora-10gb
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# Train small to fit 10GB
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sequence_len: 512
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sample_packing: false
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pad_to_sequence_len: false
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adapter: qlora
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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_linear: true
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gradient_accumulation_steps: 8
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micro_batch_size: 1
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num_epochs: 1
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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bf16: auto
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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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resume_from_checkpoint:
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logging_steps: 5
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flash_attention: true
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warmup_ratio: 0.03
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evals_per_epoch: 2
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saves_per_epoch: 1
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weight_decay: 0.0
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# Enable router logits if you want aux loss/analysis
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model_config:
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output_router_logits: true
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special_tokens:
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