9d5c95db6f
* fix for parallelism config from trainer * fix handling of parallelism_config w accelerate * add todo for removal * update to latest axolotl-contribs-mit for optimizer fix too * synchronize training after checkpoint save * dir spelling * use latest accelerate main * fix to not use partial state parallelism_config * more fixeS * use most recent accelerate fix * fix cpu_ram_efficient_loading to meta devices from rank 0 to prevent CPU RAM oom * improve handling of broadcasting fsdp2 state dict * support for openai chat template with thinking key as the reasoning trace * address PR feedback * refactor to remove dependency on PartialState for parallelism config * bump accelerate, gptoss fixes * limit meta fixes to fsdp2 for now * fixes for gpt oss * fixup examples, don't use cpu-ram-efficient-loading for now * remove problematic barrier * patch parallelism config * reorder comparison * device mesh fixes * make pure CP work * lint
47 lines
883 B
YAML
47 lines
883 B
YAML
base_model: Qwen/Qwen3-8B
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plugins:
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
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dp_shard_size: 2
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# dp_replicate_size: 1
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context_parallel_size: 2
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tensor_parallel_size: 2
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dataset_prepared_path: last_run_prepared
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fsdp_version: 2
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fsdp_config:
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offload_params: false
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state_dict_type: FULL_STATE_DICT
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auto_wrap_policy: TRANSFORMER_BASED_WRAP
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transformer_layer_cls_to_wrap: Qwen3DecoderLayer
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reshard_after_forward: true
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datasets:
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- path: tatsu-lab/alpaca
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type: alpaca
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output_dir: ./outputs/ndp-out/
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sequence_len: 8192
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sample_packing: true
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flash_attention: true
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gradient_accumulation_steps: 1
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micro_batch_size: 1 # must be 1 when using context parallel
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num_epochs: 2
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optimizer: adamw_torch_fused
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lr_scheduler: constant_with_warmup
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learning_rate: 2e-6
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bf16: true
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tf32: true
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logging_steps: 1
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saves_per_epoch: 1
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warmup_ratio: 0.1
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special_tokens:
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