90 lines
1.6 KiB
YAML
90 lines
1.6 KiB
YAML
base_model: ./mistralai/Mistral-7B-v0.1-chatml
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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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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datasets:
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- path: andysalerno/ansalern-nectar-inputoutput
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type:
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field_instruction: input
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field_output: output
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format: "{instruction}"
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no_input_format: "{instruction}"
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.005
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output_dir: ./qlora-out
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adapter: qlora
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lora_model_dir:
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sequence_len: 8192
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sample_packing: true # was true
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eval_sample_packing: false
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pad_to_sequence_len: true
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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lora_modules_to_save: ['embed_tokens', 'lm_head']
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lora_target_modules:
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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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- embed_tokens
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- lm_head
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wandb_project: axolotl
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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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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.00005
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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: true
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early_stopping_patience: 3
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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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loss_watchdog_threshold: 5.0
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loss_watchdog_patience: 3
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warmup_steps: 0.1
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eval_steps: 50
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eval_table_size:
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eval_table_max_new_tokens: 128
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save_steps: 300
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max_steps: 300
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<|im_start|>"
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eos_token: "<|im_end|>"
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unk_token: "<unk>" |