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70b.yml
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## model
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base_model: /home/quixi/Mango/models/Sao10K_Llama-3.3-70B-Vulpecula-r1
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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## qlora
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load_in_8bit: false
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load_in_4bit: True
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strict: false
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## Lora
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adapter: lora
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lora_model_dir:
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lora_r: 32
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lora_alpha: 64
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lora_dropout: 0.0
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peft_use_rslora: true
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lora_target_modules:
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lora_mlp_kernel: false
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lora_qkv_kernel: false
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lora_o_kernel: false
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lora_target_linear: true
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# - gate_proj
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# - down_proj
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# - up_proj
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# - q_proj
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# - v_proj
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# - k_proj
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# - o_proj
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## data
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datasets:
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- path: Delta-Vector/Orion-Books-V2-ShareGPT
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type: dan-chat-advanced-llama3
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- path: PocketDoc/Dans-Prosemaxx-RepRemover-1
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type: dan-chat-advanced-llama3
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- path: Delta-Vector/Orion-Personamaxx-RP
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type: dan-chat-advanced-llama3
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shuffle_merged_datasets: true
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dataset_prepared_path: base-dataset_prepared
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val_set_size: 0.0
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output_dir: ./SFT-Vulpecula
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## Liger + CCE
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_layer_norm: true
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liger_glu_activation: true
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liger_fused_linear_cross_entropy: false
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cut_cross_entropy: true
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## CTX settings
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sequence_len: 4096
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sample_packing: true
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eval_sample_packing: false
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pad_to_sequence_len: true
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## WandB
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wandb_project: Francois
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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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## evals
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#evals_per_epoch: 4
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#eval_table_size:
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#eval_max_new_tokens: 128
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## hparams
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gradient_accumulation_steps: 2
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micro_batch_size: 1
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num_epochs: 2
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optimizer: adamw_torch_fused
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#optim_args: proj=random,rank=1,scale=128.0,scale_type=tensor,update_proj_gap=200
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#optim_target_modules:
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# - .*.attn.*
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# - .*.mlp.*
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lr_scheduler: cosine
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learning_rate: 1e-5
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warmup_steps: 50
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weight_decay: 0.0025
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## max grad norm
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max_grad_norm: 0.001
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: offload
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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s2_attention:
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saves_per_epoch: 2
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debug:
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#deepspeed: ./deepspeed_configs/zero3_bf16_cpuoffload_all.json
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#fsdp:
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#fsdp_config:
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fsdp:
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- full_shard
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- auto_wrap
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fsdp_config:
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fsdp_limit_all_gathers: true
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fsdp_sync_module_states: true
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fsdp_offload_params: true
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fsdp_use_orig_params: false
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fsdp_cpu_ram_efficient_loading: true
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fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
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fsdp_state_dict_type: FULL_STATE_DICT
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fsdp_sharding_strategy: FULL_SHARD
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special_tokens:
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pad_token: <|finetune_right_pad_id|>
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eos_token: <|eot_id|>
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