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dataset_args:
path: argilla/10k_prompts_dpo
format_args:
prompt_format: zephyr
model_args:
pretrained_model_name_or_path: alignment-handbook/zephyr-7b-sft-full
torch_dtype: float16
quantization_config:
quant_method: bitsandbytes
load_in_4bit: true
peft_config:
r: 16
lora_alpha: 16
lora_dropout: 0.05
bias: none
task_type: CAUSAL_LM
target_modules:
- k_proj
- gate_proj
- v_proj
- up_proj
- q_proj
- o_proj
- down_proj
wandb_args:
entity: argilla-io
project: dibt-dpo
name: zephyr-7b-lora-dpo-dibt-openhermes-params-v0
training_args:
# `trl.DPOTrainer`
beta: 0.1
max_length: 1536
max_prompt_length: 1024
loss_type: sigmoid
# `transformers.Trainer`
bf16: true
do_eval: true
do_train: true
evaluation_strategy: steps
eval_steps: 20
gradient_accumulation_steps: 4
gradient_checkpointing: true
hub_model_id: plaguss/zephyr-7b-lora-dpo-dibt-v0
hub_model_revision: v0
hub_strategy: every_save
hub_private_repo: true
push_to_hub: true
learning_rate: 5.0e-5
logging_steps: 10
lr_scheduler_type: cosine
num_train_epochs: 2
optim: paged_adamw_32bit
output_dir: data/zephyr-7b-sft-lora-dpo-v0
load_best_model_at_end: true
metric_for_best_model: rewards/accuracies
greater_is_better: true
per_device_train_batch_size: 4
per_device_eval_batch_size: 16
save_strategy: steps
save_total_limit: null
seed: 42
warmup_ratio: 0.1
report_to:
- wandb
use_accelerate: false
use_unsloth: false