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* add phi full ft example * Add readme to point out that deepspeed should be used * zero1 is better than zero2 for phi
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# Phi | ||
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Due to some nuances with the phi code, please use deepspeed when training phi. | ||
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```shell | ||
accelerate launch scripts/finetune.py examples/phi/phi-ft.yml --deepspeed deepspeed/zero1.json | ||
``` |
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base_model: microsoft/phi-1_5 | ||
base_model_config: microsoft/phi-1_5 | ||
model_type: AutoModelForCausalLM | ||
tokenizer_type: AutoTokenizer | ||
is_llama_derived_model: false | ||
trust_remote_code: true | ||
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load_in_8bit: false | ||
load_in_4bit: false | ||
strict: false | ||
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datasets: | ||
- path: garage-bAInd/Open-Platypus | ||
type: alpaca | ||
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dataset_prepared_path: last_run_prepared | ||
val_set_size: 0.05 | ||
output_dir: ./phi-sft-out | ||
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sequence_len: 2048 | ||
sample_packing: false # does not work with phi | ||
pad_to_sequence_len: | ||
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adapter: | ||
lora_model_dir: | ||
lora_r: | ||
lora_alpha: | ||
lora_dropout: | ||
lora_target_linear: | ||
lora_fan_in_fan_out: | ||
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wandb_project: | ||
wandb_entity: | ||
wandb_watch: | ||
wandb_run_id: | ||
wandb_log_model: | ||
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gradient_accumulation_steps: 2 | ||
micro_batch_size: 1 | ||
num_epochs: 4 | ||
optimizer: adamw_bnb_8bit | ||
adam_beta2: 0.95 | ||
adam_epsilon: 0.00001 | ||
max_grad_norm: 1.0 | ||
lr_scheduler: cosine | ||
learning_rate: 0.000003 | ||
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train_on_inputs: false | ||
group_by_length: true | ||
bf16: true | ||
fp16: false | ||
tf32: true | ||
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gradient_checkpointing: | ||
early_stopping_patience: | ||
resume_from_checkpoint: | ||
local_rank: | ||
logging_steps: 1 | ||
xformers_attention: | ||
flash_attention: | ||
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warmup_steps: 100 | ||
eval_steps: 0.05 | ||
save_steps: | ||
debug: | ||
deepspeed: | ||
weight_decay: 0.1 | ||
fsdp: | ||
fsdp_config: | ||
resize_token_embeddings_to_32x: true | ||
special_tokens: | ||
bos_token: "<|endoftext|>" | ||
eos_token: "<|endoftext|>" | ||
unk_token: "<|endoftext|>" | ||
pad_token: "<|endoftext|>" |