22810c97b7
* use warmup_ratio as a better default than warmup steps since it's data dependent * replace remainder of warmup_steps
52 lines
1.0 KiB
YAML
52 lines
1.0 KiB
YAML
base_model: huggyllama/llama-7b
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# optionally might have model_type or tokenizer_type
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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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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datasets:
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- path: openaccess-ai-collective/jeopardy
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type: jeopardy
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dataset_prepared_path:
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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: 512
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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:
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lora_target_modules:
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lora_fan_in_fan_out: false
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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/jeopardy-bot-7b
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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: 0.00003
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bf16: auto
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tf32: true
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resume_from_checkpoint:
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logging_steps: 5
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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_ratio: 0.1
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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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tokens:
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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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