Add QAT NVFP4 configs for blogpost (#3280) [skip ci]
* add configs for blogpost * fix configs * fixing baseline configs
This commit is contained in:
67
examples/qat_nvfp4/Gemma3-12B_baseline.yml
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67
examples/qat_nvfp4/Gemma3-12B_baseline.yml
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@@ -0,0 +1,67 @@
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base_model: google/gemma-3-12b-it
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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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load_in_8bit: false
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load_in_4bit: false
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strict: false
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_glu_activation: true
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liger_layer_norm: true
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liger_fused_linear_cross_entropy: true
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seed: 42
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chat_template: gemma3
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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/out_gemma/
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sequence_len: 8096
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sample_packing: true
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flash_attention: true
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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: 1
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micro_batch_size: 16
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num_epochs: 1
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 4e-5
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bf16: true
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tf32: true
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resume_from_checkpoint:
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logging_steps: 1
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# evals_per_epoch: 1
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saves_per_epoch: 1
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warmup_ratio: 0.1
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weight_decay: 0.0
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fsdp_version: 2
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fsdp_config:
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offload_params: false
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cpu_ram_efficient_loading: true
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auto_wrap_policy: TRANSFORMER_BASED_WRAP
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transformer_layer_cls_to_wrap: Gemma3DecoderLayer
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state_dict_type: FULL_STATE_DICT
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sharding_strategy: FULL_SHARD
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reshard_after_forward: true
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activation_checkpointing: true
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special_tokens:
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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72
examples/qat_nvfp4/Gemma3-12B_qat.yml
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72
examples/qat_nvfp4/Gemma3-12B_qat.yml
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@@ -0,0 +1,72 @@
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base_model: google/gemma-3-12b-it
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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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load_in_8bit: false
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load_in_4bit: false
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strict: false
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_glu_activation: true
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liger_layer_norm: true
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liger_fused_linear_cross_entropy: true
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seed: 42
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chat_template: gemma3
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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/qat_out_gemma/
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sequence_len: 8096
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sample_packing: true
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flash_attention: true
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qat:
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activation_dtype: nvfp4
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weight_dtype: nvfp4
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group_size: 16 # only group_size of 16 is supported with nvfp4
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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: 1
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micro_batch_size: 16
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num_epochs: 1
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 4e-5
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bf16: true
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tf32: true
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resume_from_checkpoint:
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logging_steps: 1
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evals_per_epoch: 1
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saves_per_epoch: 1
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warmup_ratio: 0.1
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weight_decay: 0.0
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fsdp_version: 2
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fsdp_config:
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offload_params: false
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cpu_ram_efficient_loading: true
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auto_wrap_policy: TRANSFORMER_BASED_WRAP
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transformer_layer_cls_to_wrap: Gemma3DecoderLayer
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state_dict_type: FULL_STATE_DICT
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sharding_strategy: FULL_SHARD
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reshard_after_forward: true
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activation_checkpointing: true
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special_tokens:
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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67
examples/qat_nvfp4/Math-Gemma3-12B_baseline.yml
Normal file
67
examples/qat_nvfp4/Math-Gemma3-12B_baseline.yml
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@@ -0,0 +1,67 @@
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base_model: google/gemma-3-12b-it
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# Math finetuning configuration for Gemma3-12B
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# hub_model_id: username/custom_model_name
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_glu_activation: true
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liger_layer_norm: true
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liger_fused_linear_cross_entropy: true
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seed: 42
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chat_template: gemma3
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datasets:
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- path: AI-MO/NuminaMath-CoT
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type: chat_template
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output_dir: ./outputs/out_math_gemma/
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sequence_len: 4096
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sample_packing: true
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flash_attention: true
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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: 1
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micro_batch_size: 8
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num_epochs: 1
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 3e-5
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bf16: true
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tf32: true
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resume_from_checkpoint:
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logging_steps: 1
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# evals_per_epoch: 1
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saves_per_epoch: 1
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warmup_ratio: 0.1
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weight_decay: 0.0
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fsdp_version: 2
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fsdp_config:
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offload_params: false
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cpu_ram_efficient_loading: true
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auto_wrap_policy: TRANSFORMER_BASED_WRAP
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transformer_layer_cls_to_wrap: Gemma3DecoderLayer
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state_dict_type: FULL_STATE_DICT
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sharding_strategy: FULL_SHARD
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reshard_after_forward: true
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activation_checkpointing: true
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special_tokens:
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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72
examples/qat_nvfp4/Math-Gemma3-12B_qat.yml
Normal file
72
examples/qat_nvfp4/Math-Gemma3-12B_qat.yml
Normal file
@@ -0,0 +1,72 @@
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base_model: google/gemma-3-12b-it
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# Math finetuning configuration for Gemma3-12B
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# hub_model_id: username/custom_model_name
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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||||
liger_rope: true
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||||
liger_rms_norm: true
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||||
liger_glu_activation: true
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liger_layer_norm: true
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liger_fused_linear_cross_entropy: true
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seed: 42
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chat_template: gemma3
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datasets:
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- path: AI-MO/NuminaMath-CoT
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type: chat_template
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output_dir: ./outputs/qat_out_math_gemma/
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sequence_len: 4096
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sample_packing: true
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flash_attention: true
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qat:
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activation_dtype: nvfp4
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weight_dtype: nvfp4
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group_size: 16 # only group_size of 16 is supported with nvfp4
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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: 1
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micro_batch_size: 8
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num_epochs: 1
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 3e-5
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bf16: true
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tf32: true
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resume_from_checkpoint:
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logging_steps: 1
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# evals_per_epoch: 1
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saves_per_epoch: 1
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warmup_ratio: 0.1
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weight_decay: 0.0
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fsdp_version: 2
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fsdp_config:
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offload_params: false
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cpu_ram_efficient_loading: true
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auto_wrap_policy: TRANSFORMER_BASED_WRAP
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transformer_layer_cls_to_wrap: Gemma3DecoderLayer
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state_dict_type: FULL_STATE_DICT
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sharding_strategy: FULL_SHARD
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reshard_after_forward: true
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activation_checkpointing: true
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special_tokens:
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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||||
68
examples/qat_nvfp4/Math-Gemma3-27B_baseline.yml
Normal file
68
examples/qat_nvfp4/Math-Gemma3-27B_baseline.yml
Normal file
@@ -0,0 +1,68 @@
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base_model: google/gemma-3-27b-it
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# Math finetuning configuration for Gemma3-27B
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# hub_model_id: username/custom_model_name
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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||||
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||||
plugins:
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||||
- axolotl.integrations.liger.LigerPlugin
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||||
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||||
liger_rope: true
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||||
liger_rms_norm: true
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||||
liger_glu_activation: true
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||||
liger_layer_norm: true
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||||
liger_fused_linear_cross_entropy: true
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||||
seed: 42
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chat_template: gemma3
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datasets:
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- path: AI-MO/NuminaMath-CoT
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type: chat_template
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output_dir: ./outputs/out_math_gemma27/
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sequence_len: 4096
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sample_packing: true
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flash_attention: true
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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: 1
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micro_batch_size: 16
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num_epochs: 1
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 5e-6
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eta_min: 7e-7
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bf16: true
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tf32: true
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resume_from_checkpoint:
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logging_steps: 1
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# evals_per_epoch: 1
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saves_per_epoch: 1
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warmup_ratio: 0.1
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weight_decay: 0.0
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fsdp_version: 2
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fsdp_config:
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offload_params: false
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||||
cpu_ram_efficient_loading: true
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auto_wrap_policy: TRANSFORMER_BASED_WRAP
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transformer_layer_cls_to_wrap: Gemma3DecoderLayer
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state_dict_type: FULL_STATE_DICT
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sharding_strategy: FULL_SHARD
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reshard_after_forward: true
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activation_checkpointing: true
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special_tokens:
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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||||
73
examples/qat_nvfp4/Math-Gemma3-27B_qat.yml
Normal file
73
examples/qat_nvfp4/Math-Gemma3-27B_qat.yml
Normal file
@@ -0,0 +1,73 @@
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||||
base_model: google/gemma-3-27b-it
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# Math finetuning configuration for Gemma3-27B
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# hub_model_id: username/custom_model_name
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||||
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load_in_8bit: false
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||||
load_in_4bit: false
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||||
strict: false
|
||||
|
||||
plugins:
|
||||
- axolotl.integrations.liger.LigerPlugin
|
||||
|
||||
liger_rope: true
|
||||
liger_rms_norm: true
|
||||
liger_glu_activation: true
|
||||
liger_layer_norm: true
|
||||
liger_fused_linear_cross_entropy: true
|
||||
seed: 42
|
||||
chat_template: gemma3
|
||||
datasets:
|
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- path: AI-MO/NuminaMath-CoT
|
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type: chat_template
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||||
|
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output_dir: ./outputs/qat_out_math_gemma27/
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||||
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sequence_len: 4096
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sample_packing: true
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||||
flash_attention: true
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||||
|
||||
qat:
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||||
activation_dtype: nvfp4
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||||
weight_dtype: nvfp4
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||||
group_size: 16 # only group_size of 16 is supported with nvfp4
|
||||
|
||||
wandb_entity:
|
||||
wandb_watch:
|
||||
wandb_name:
|
||||
wandb_log_model:
|
||||
|
||||
gradient_accumulation_steps: 1
|
||||
micro_batch_size: 16
|
||||
|
||||
num_epochs: 1
|
||||
optimizer: adamw_torch_fused
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 5e-6
|
||||
eta_min: 7e-7
|
||||
|
||||
bf16: true
|
||||
tf32: true
|
||||
|
||||
resume_from_checkpoint:
|
||||
logging_steps: 1
|
||||
|
||||
# evals_per_epoch: 1
|
||||
saves_per_epoch: 1
|
||||
|
||||
warmup_ratio: 0.1
|
||||
weight_decay: 0.0
|
||||
fsdp_version: 2
|
||||
|
||||
fsdp_config:
|
||||
offload_params: false
|
||||
cpu_ram_efficient_loading: true
|
||||
auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
||||
transformer_layer_cls_to_wrap: Gemma3DecoderLayer
|
||||
state_dict_type: FULL_STATE_DICT
|
||||
sharding_strategy: FULL_SHARD
|
||||
reshard_after_forward: true
|
||||
activation_checkpointing: true
|
||||
|
||||
special_tokens:
|
||||
|
||||
# save_first_step: true # uncomment this to validate checkpoint saving works with your config
|
||||
67
examples/qat_nvfp4/Math-Qwen2.5-72B_baseline.yml
Normal file
67
examples/qat_nvfp4/Math-Qwen2.5-72B_baseline.yml
Normal file
@@ -0,0 +1,67 @@
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||||
base_model: Qwen/Qwen2.5-72B
|
||||
# Math finetuning configuration for Qwen2.5-72B (non-instruct)
|
||||
# hub_model_id: username/custom_model_name
|
||||
|
||||
load_in_8bit: false
|
||||
load_in_4bit: false
|
||||
strict: false
|
||||
|
||||
plugins:
|
||||
- axolotl.integrations.liger.LigerPlugin
|
||||
|
||||
liger_rope: true
|
||||
liger_rms_norm: true
|
||||
liger_glu_activation: true
|
||||
liger_layer_norm: true
|
||||
liger_fused_linear_cross_entropy: true
|
||||
seed: 42
|
||||
chat_template: qwen_25
|
||||
datasets:
|
||||
- path: AI-MO/NuminaMath-CoT
|
||||
type: chat_template
|
||||
|
||||
output_dir: ./outputs/out_math_72b/
|
||||
|
||||
sequence_len: 4096
|
||||
sample_packing: true
|
||||
flash_attention: true
|
||||
|
||||
wandb_entity:
|
||||
wandb_watch:
|
||||
wandb_name:
|
||||
wandb_log_model:
|
||||
|
||||
gradient_accumulation_steps: 1
|
||||
micro_batch_size: 8
|
||||
num_epochs: 1
|
||||
optimizer: adamw_torch_fused
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 5e-6
|
||||
eta_min: 7e-7
|
||||
|
||||
bf16: true
|
||||
tf32: true
|
||||
|
||||
resume_from_checkpoint:
|
||||
logging_steps: 1
|
||||
|
||||
# evals_per_epoch: 1
|
||||
saves_per_epoch: 1
|
||||
|
||||
warmup_ratio: 0.1
|
||||
weight_decay: 0.0
|
||||
fsdp_version: 2
|
||||
|
||||
fsdp_config:
|
||||
offload_params: false
|
||||
cpu_ram_efficient_loading: true
|
||||
auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
||||
transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
||||
state_dict_type: FULL_STATE_DICT
|
||||
sharding_strategy: FULL_SHARD
|
||||
reshard_after_forward: true
|
||||
activation_checkpointing: true
|
||||
|
||||
special_tokens:
|
||||
|
||||
# save_first_step: true # uncomment this to validate checkpoint saving works with your config
|
||||
72
examples/qat_nvfp4/Math-Qwen2.5-72B_qat.yml
Normal file
72
examples/qat_nvfp4/Math-Qwen2.5-72B_qat.yml
Normal file
@@ -0,0 +1,72 @@
|
||||
base_model: Qwen/Qwen2.5-72B
|
||||
# Math finetuning configuration for Qwen2.5-72B (non-instruct)
|
||||
# hub_model_id: username/custom_model_name
|
||||
|
||||
load_in_8bit: false
|
||||
load_in_4bit: false
|
||||
strict: false
|
||||
|
||||
plugins:
|
||||
- axolotl.integrations.liger.LigerPlugin
|
||||
|
||||
liger_rope: true
|
||||
liger_rms_norm: true
|
||||
liger_glu_activation: true
|
||||
liger_layer_norm: true
|
||||
liger_fused_linear_cross_entropy: true
|
||||
seed: 42
|
||||
chat_template: qwen_25
|
||||
datasets:
|
||||
- path: AI-MO/NuminaMath-CoT
|
||||
type: chat_template
|
||||
|
||||
output_dir: ./outputs/qat_out_math_72b/
|
||||
|
||||
sequence_len: 4096
|
||||
sample_packing: true
|
||||
flash_attention: true
|
||||
|
||||
qat:
|
||||
activation_dtype: nvfp4
|
||||
weight_dtype: nvfp4
|
||||
group_size: 16 # only group_size of 16 is supported with nvfp4
|
||||
|
||||
wandb_entity:
|
||||
wandb_watch:
|
||||
wandb_name:
|
||||
wandb_log_model:
|
||||
|
||||
gradient_accumulation_steps: 1
|
||||
micro_batch_size: 8
|
||||
num_epochs: 1
|
||||
optimizer: adamw_torch_fused
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 5e-6
|
||||
eta_min: 7e-7
|
||||
|
||||
bf16: true
|
||||
tf32: true
|
||||
|
||||
resume_from_checkpoint:
|
||||
logging_steps: 1
|
||||
|
||||
# evals_per_epoch: 1
|
||||
saves_per_epoch: 1
|
||||
|
||||
warmup_ratio: 0.1
|
||||
weight_decay: 0.0
|
||||
fsdp_version: 2
|
||||
|
||||
fsdp_config:
|
||||
offload_params: false
|
||||
cpu_ram_efficient_loading: true
|
||||
auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
||||
transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
||||
state_dict_type: FULL_STATE_DICT
|
||||
sharding_strategy: FULL_SHARD
|
||||
reshard_after_forward: true
|
||||
activation_checkpointing: true
|
||||
|
||||
special_tokens:
|
||||
|
||||
# save_first_step: true # uncomment this to validate checkpoint saving works with your config
|
||||
67
examples/qat_nvfp4/Qwen2.5-72B_baseline.yml
Normal file
67
examples/qat_nvfp4/Qwen2.5-72B_baseline.yml
Normal file
@@ -0,0 +1,67 @@
|
||||
base_model: Qwen/Qwen2.5-72B
|
||||
# Alpaca finetuning configuration for Qwen2.5-72B
|
||||
# hub_model_id: username/custom_model_name
|
||||
|
||||
load_in_8bit: false
|
||||
load_in_4bit: false
|
||||
strict: false
|
||||
|
||||
plugins:
|
||||
- axolotl.integrations.liger.LigerPlugin
|
||||
|
||||
liger_rope: true
|
||||
liger_rms_norm: true
|
||||
liger_glu_activation: true
|
||||
liger_layer_norm: true
|
||||
liger_fused_linear_cross_entropy: true
|
||||
seed: 42
|
||||
chat_template: qwen_25
|
||||
datasets:
|
||||
- path: tatsu-lab/alpaca
|
||||
type: alpaca
|
||||
|
||||
output_dir: ./outputs/out_qwen72b/
|
||||
|
||||
sequence_len: 8096
|
||||
sample_packing: true
|
||||
flash_attention: true
|
||||
|
||||
wandb_entity:
|
||||
wandb_watch:
|
||||
wandb_name:
|
||||
wandb_log_model:
|
||||
|
||||
gradient_accumulation_steps: 1
|
||||
micro_batch_size: 16
|
||||
|
||||
num_epochs: 1
|
||||
optimizer: adamw_torch_fused
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 2e-5
|
||||
|
||||
bf16: true
|
||||
tf32: true
|
||||
|
||||
resume_from_checkpoint:
|
||||
logging_steps: 1
|
||||
|
||||
# evals_per_epoch: 1
|
||||
saves_per_epoch: 1
|
||||
|
||||
warmup_ratio: 0.1
|
||||
weight_decay: 0.0
|
||||
fsdp_version: 2
|
||||
|
||||
fsdp_config:
|
||||
offload_params: false
|
||||
cpu_ram_efficient_loading: true
|
||||
auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
||||
transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
||||
state_dict_type: FULL_STATE_DICT
|
||||
sharding_strategy: FULL_SHARD
|
||||
reshard_after_forward: true
|
||||
activation_checkpointing: true
|
||||
|
||||
special_tokens:
|
||||
|
||||
# save_first_step: true # uncomment this to validate checkpoint saving works with your config
|
||||
72
examples/qat_nvfp4/Qwen2.5-72B_qat.yml
Normal file
72
examples/qat_nvfp4/Qwen2.5-72B_qat.yml
Normal file
@@ -0,0 +1,72 @@
|
||||
base_model: Qwen/Qwen2.5-72B
|
||||
# Alpaca finetuning configuration for Qwen2.5-72B
|
||||
# hub_model_id: username/custom_model_name
|
||||
|
||||
load_in_8bit: false
|
||||
load_in_4bit: false
|
||||
strict: false
|
||||
|
||||
plugins:
|
||||
- axolotl.integrations.liger.LigerPlugin
|
||||
|
||||
liger_rope: true
|
||||
liger_rms_norm: true
|
||||
liger_glu_activation: true
|
||||
liger_layer_norm: true
|
||||
liger_fused_linear_cross_entropy: true
|
||||
seed: 42
|
||||
chat_template: qwen_25
|
||||
datasets:
|
||||
- path: tatsu-lab/alpaca
|
||||
type: alpaca
|
||||
|
||||
output_dir: ./outputs/qat_out_qwen72b/
|
||||
|
||||
sequence_len: 8096
|
||||
sample_packing: true
|
||||
flash_attention: true
|
||||
|
||||
qat:
|
||||
activation_dtype: nvfp4
|
||||
weight_dtype: nvfp4
|
||||
group_size: 16 # only group_size of 16 is supported with nvfp4
|
||||
|
||||
wandb_entity:
|
||||
wandb_watch:
|
||||
wandb_name:
|
||||
wandb_log_model:
|
||||
|
||||
gradient_accumulation_steps: 1
|
||||
micro_batch_size: 16
|
||||
|
||||
num_epochs: 1
|
||||
optimizer: adamw_torch_fused
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 2e-5
|
||||
|
||||
bf16: true
|
||||
tf32: true
|
||||
|
||||
resume_from_checkpoint:
|
||||
logging_steps: 1
|
||||
|
||||
# evals_per_epoch: 1
|
||||
saves_per_epoch: 1
|
||||
|
||||
warmup_ratio: 0.1
|
||||
weight_decay: 0.0
|
||||
fsdp_version: 2
|
||||
|
||||
fsdp_config:
|
||||
offload_params: false
|
||||
cpu_ram_efficient_loading: true
|
||||
auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
||||
transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
||||
state_dict_type: FULL_STATE_DICT
|
||||
sharding_strategy: FULL_SHARD
|
||||
reshard_after_forward: true
|
||||
activation_checkpointing: true
|
||||
|
||||
special_tokens:
|
||||
|
||||
# save_first_step: true # uncomment this to validate checkpoint saving works with your config
|
||||
Reference in New Issue
Block a user