more sane defaults for openllama 3b used for quickstarts (#602)
Browse files* more sane defaults for openllama 3b used for quickstarts
* don't use bf16 for quickstart to simplify gpu compatibility
* use the update openlm-research/open_llama_3b_v2 models
- examples/openllama-3b/config.yml +10 -10
- examples/openllama-3b/lora.yml +12 -12
- examples/openllama-3b/qlora.yml +15 -15
examples/openllama-3b/config.yml
CHANGED
@@ -1,5 +1,5 @@
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-
base_model: openlm-research/
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-
base_model_config: openlm-research/
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: false
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@@ -13,8 +13,8 @@ dataset_prepared_path: last_run_prepared
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val_set_size: 0.02
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adapter:
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lora_model_dir:
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-
sequence_len:
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-
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lora_r:
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lora_alpha:
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lora_dropout:
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@@ -29,11 +29,11 @@ wandb_log_model:
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output_dir: ./openllama-out
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gradient_accumulation_steps: 1
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micro_batch_size: 1
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-
num_epochs:
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optimizer: adamw_bnb_8bit
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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: false
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float16: true
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@@ -45,12 +45,12 @@ 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:
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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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+
base_model: openlm-research/open_llama_3b_v2
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+
base_model_config: openlm-research/open_llama_3b_v2
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: false
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val_set_size: 0.02
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adapter:
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lora_model_dir:
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+
sequence_len: 1024
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+
sample_packing: true
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lora_r:
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lora_alpha:
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lora_dropout:
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output_dir: ./openllama-out
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gradient_accumulation_steps: 1
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micro_batch_size: 1
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+
num_epochs: 4
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optimizer: adamw_bnb_8bit
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torchdistx_path:
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lr_scheduler: cosine
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+
learning_rate: 0.000003
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train_on_inputs: false
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group_by_length: false
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float16: true
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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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gptq_groupsize:
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gptq_model_v1:
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+
warmup_steps: 20
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+
eval_steps: 0.05
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save_steps:
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debug:
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deepspeed:
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examples/openllama-3b/lora.yml
CHANGED
@@ -1,5 +1,5 @@
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-
base_model: openlm-research/
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-
base_model_config: openlm-research/
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3 |
model_type: LlamaForCausalLM
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4 |
tokenizer_type: LlamaTokenizer
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5 |
load_in_8bit: true
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@@ -13,8 +13,8 @@ dataset_prepared_path: last_run_prepared
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val_set_size: 0.02
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adapter: lora
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lora_model_dir:
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-
sequence_len:
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-
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.0
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@@ -33,9 +33,9 @@ wandb_watch:
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wandb_run_id:
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wandb_log_model:
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output_dir: ./lora-out
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-
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-
micro_batch_size:
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-
num_epochs:
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optimizer: adamw_bnb_8bit
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torchdistx_path:
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lr_scheduler: cosine
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@@ -50,16 +50,16 @@ 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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54 |
-
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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special_tokens:
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+
base_model: openlm-research/open_llama_3b_v2
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+
base_model_config: openlm-research/open_llama_3b_v2
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: true
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val_set_size: 0.02
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adapter: lora
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lora_model_dir:
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+
sequence_len: 1024
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sample_packing: true
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.0
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wandb_run_id:
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wandb_log_model:
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output_dir: ./lora-out
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+
gradient_accumulation_steps: 1
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+
micro_batch_size: 2
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+
num_epochs: 4
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optimizer: adamw_bnb_8bit
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torchdistx_path:
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lr_scheduler: cosine
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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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gptq_groupsize:
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gptq_model_v1:
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+
warmup_steps: 20
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+
eval_steps: 0.05
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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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examples/openllama-3b/qlora.yml
CHANGED
@@ -1,5 +1,5 @@
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1 |
-
base_model: openlm-research/
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2 |
-
base_model_config: openlm-research/
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3 |
model_type: LlamaForCausalLM
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4 |
tokenizer_type: LlamaTokenizer
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load_in_8bit: false
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@@ -13,8 +13,8 @@ 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:
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-
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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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@@ -27,33 +27,33 @@ 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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-
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-
micro_batch_size:
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-
num_epochs:
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optimizer: paged_adamw_32bit
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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: false
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-
bf16:
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-
fp16:
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-
tf32:
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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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logging_steps: 1
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-
xformers_attention:
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-
flash_attention:
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gptq_groupsize:
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gptq_model_v1:
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51 |
-
warmup_steps:
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52 |
-
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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57 |
fsdp:
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fsdp_config:
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special_tokens:
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+
base_model: openlm-research/open_llama_3b_v2
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+
base_model_config: openlm-research/open_llama_3b_v2
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: false
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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: 1024
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+
sample_packing: true
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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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wandb_run_id:
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wandb_log_model:
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output_dir: ./qlora-out
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+
gradient_accumulation_steps: 1
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+
micro_batch_size: 2
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+
num_epochs: 4
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optimizer: paged_adamw_32bit
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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: false
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+
bf16: false
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+
fp16: true
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+
tf32: false
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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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logging_steps: 1
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+
xformers_attention:
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+
flash_attention: true
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gptq_groupsize:
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gptq_model_v1:
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+
warmup_steps: 20
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+
eval_steps: 0.05
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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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