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axolotl/examples/gpt-oss/gpt-oss-20b-fft-fsdp2.yaml
Wing Lian 9d5c95db6f Add support for Accelerate CP, ND examples, and fix for parallel config w fsdp (#3019)
* 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
2025-08-07 21:22:15 -04:00

66 lines
1.3 KiB
YAML

base_model: openai/gpt-oss-20b
use_kernels: false
model_quantization_config: Mxfp4Config
model_quantization_config_kwargs:
dequantize: true
plugins:
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
experimental_skip_move_to_device: true # prevent OOM by NOT putting model to GPU before sharding
datasets:
- path: HuggingFaceH4/Multilingual-Thinking
type: chat_template
field_thinking: thinking
template_thinking_key: thinking
dataset_prepared_path: last_run_prepared
val_set_size: 0
output_dir: ./outputs/gpt-oss-out/
sequence_len: 4096
sample_packing: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_torch_8bit
lr_scheduler: constant_with_warmup
learning_rate: 2e-5
bf16: true
tf32: true
flash_attention: true
attn_implementation: kernels-community/vllm-flash-attn3
gradient_checkpointing: true
activation_offloading: true
logging_steps: 1
saves_per_epoch: 1
warmup_ratio: 0.03
special_tokens:
eot_tokens:
- "<|end|>"
- "<|return|>"
fsdp_version: 2
fsdp_config:
offload_params: false
state_dict_type: SHARDED_STATE_DICT
auto_wrap_policy: TRANSFORMER_BASED_WRAP
transformer_layer_cls_to_wrap: GptOssDecoderLayer
reshard_after_forward: true
# cpu_ram_efficient_loading: true