9f824ef76a
* simplify the example configs to be more minimal and less daunting * drop empty s2_attention from example yamls
53 lines
1006 B
YAML
53 lines
1006 B
YAML
base_model: cerebras/Cerebras-GPT-1.3B
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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: 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:
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val_set_size: 0.05
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adapter: qlora
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lora_model_dir:
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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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wandb_project:
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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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output_dir: ./outputs/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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bf16: auto
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tf32: true
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gradient_checkpointing: true
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resume_from_checkpoint:
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logging_steps: 1
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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: 10
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evals_per_epoch: 4
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saves_per_epoch: 1
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weight_decay: 0.1
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special_tokens:
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pad_token: "<|endoftext|>"
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