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prepared dataset caching, other misc fixes (#665)
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base_model: EleutherAI/pythia-12b-deduped
base_model_config: EleutherAI/pythia-12b-deduped
base_model_ignore_patterns: pytorch* # prefer safetensors
model_type: GPTNeoXForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
gptq: false
device_map: auto
datasets:
- path: vicgalle/alpaca-gpt4
type: alpaca
dataset_prepared_path:
val_set_size: 0.05
adapter:
lora_model_dir:
sequence_len: 2048
max_packed_sequence_len: 2048
lora_r: 64
lora_alpha: 32
lora_dropout: 0.0
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out: true # pythia/GPTNeoX lora specific
wandb_project:
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:
output_dir: ./pythia-12b
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 5
learning_rate: 0.00003
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
train_on_inputs: false
group_by_length: false
bf16: false
fp16: false
float16: true
tf32: true
flash_optimum: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
gradient_checkpointing: true
fsdp:
fsdp_config: