more pruning
Browse files
configs/cerebras_1_3B_alpaca.yml
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base_model: cerebras/Cerebras-GPT-1.3B
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: true
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datasets:
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- path: data/alpaca_data_gpt4.jsonl
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type: alpaca
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- path: data/vicuna_cleaned.jsonl
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type: sharegpt
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- path: data/gpt4-instruct-similarity-0.6-dataset.jsonl
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type: gpteacher
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- path: data/roleplay-similarity_0.6-instruct-dataset.jsonl
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type: gpteacher
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.05
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adapter: lora
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sequence_len: 2048
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_modules:
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- c_attn
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lora_fan_in_fan_out: false
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wandb_project: pythia-1.4b-lora
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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output_dir: ./lora-alpaca
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 5
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learning_rate: 0.0003
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train_on_inputs: false
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group_by_length: false
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bf16: True
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tf32: True
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gradient_checkpointing:
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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configs/galactica_1_3B.yml
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base_model: facebook/galactica-1.3b
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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datasets:
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- path: tatsu-lab/alpaca
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.1
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adapter:
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lora_model_dir:
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sequence_len: 1024
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max_packed_sequence_len: 1024
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_modules:
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- q_proj
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- v_proj
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lora_fan_in_fan_out: false
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wandb_project:
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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output_dir: ./lora-llama-alpaca
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gradient_accumulation_steps: 1
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micro_batch_size: 16
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num_epochs: 3
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learning_rate: 0.00003
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train_on_inputs: false
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group_by_length: false
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bf16: false
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tf32: false
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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tokens:
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pad_token: "[PAD]"
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bos_token: "<s>"
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eos_token: "</s>"
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unk_token: "<unk>"
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configs/gpt_neox_20b.yml
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base_model: EleutherAI/gpt-neox-20b
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base_model_ignore_patterns: pytorch* # prefer safetensors
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model_type: GPTNeoXForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: true
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datasets:
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- path: nomic-ai/gpt4all-j-prompt-generations
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type: alpaca
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shards: 4
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shards_index: 0
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.05
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adapter: lora
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lora_model_dir:
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sequence_len: 2048
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max_packed_sequence_len: 2048
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lora_r: 8
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lora_alpha: 32
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lora_dropout: 0.05
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lora_target_modules:
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- query_key_value
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lora_fan_in_fan_out: true # pythia/GPTNeoX lora specific
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wandb_project: gpt4all-neox-20b
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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output_dir: ./gpt4all-neox-20b
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 5
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learning_rate: 0.00003
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lr_scheduler: one_cycle
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train_on_inputs: false
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group_by_length: false
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bf16: True
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tf32: True
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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configs/stability_3b.yml β examples/cerebras/qlora.yml
RENAMED
@@ -1,38 +1,45 @@
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base_model:
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base_model_config:
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load_in_8bit: false
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datasets:
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- path:
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.
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adapter:
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lora_model_dir:
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sequence_len:
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max_packed_sequence_len:
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lora_r:
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lora_alpha:
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lora_dropout: 0.05
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lora_target_modules:
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-
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-
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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output_dir: ./
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micro_batch_size:
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num_epochs:
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optimizer:
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torchdistx_path:
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lr_scheduler: cosine
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learning_rate: 0.
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train_on_inputs: false
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group_by_length:
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bf16: true
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tf32: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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@@ -41,16 +48,13 @@ xformers_attention: true
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flash_attention:
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gptq_groupsize:
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gptq_model_v1:
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warmup_steps:
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eval_steps:
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save_steps:
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debug:
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deepspeed:
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weight_decay: 0.
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fsdp:
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fsdp_config:
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# bos_token: "<s>"
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# eos_token: "</s>"
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# unk_token: "<unk>"
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base_model: cerebras/Cerebras-GPT-1.3B
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base_model_config: cerebras/Cerebras-GPT-1.3B
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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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push_dataset_to_hub:
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datasets:
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- path: teknium/GPT4-LLM-Cleaned
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.01
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adapter: qlora
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lora_model_dir:
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sequence_len: 2048
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max_packed_sequence_len: 2048
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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lora_target_modules:
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- c_fc
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- c_attn
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- c_proj
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lora_target_linear:
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lora_fan_in_fan_out:
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wandb_project:
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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output_dir: ./qlora-out
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batch_size: 4
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micro_batch_size: 4
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num_epochs: 2
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optimizer: paged_adamw_8bit
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torchdistx_path:
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lr_scheduler: cosine
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learning_rate: 0.0002
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train_on_inputs: false
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group_by_length: true
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bf16: true
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fp16: false
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tf32: true
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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flash_attention:
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gptq_groupsize:
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gptq_model_v1:
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warmup_steps: 10
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eval_steps: 20
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save_steps:
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debug:
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deepspeed:
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weight_decay: 0.1
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: "<|endoftext|>"
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