metadata

library_name: transformers
license: apache-2.0
datasets:
  - nbeerbower/GreatFirewall-DPO
  - nbeerbower/Schule-DPO
  - nbeerbower/Purpura-DPO
  - nbeerbower/Arkhaios-DPO
  - jondurbin/truthy-dpo-v0.1
  - antiven0m/physical-reasoning-dpo
  - flammenai/Date-DPO-NoAsterisks
  - flammenai/Prude-Phi3-DPO
  - Atsunori/HelpSteer2-DPO
  - jondurbin/gutenberg-dpo-v0.1
  - nbeerbower/gutenberg2-dpo
  - nbeerbower/gutenberg-moderne-dpo
base_model:
  - nbeerbower/EVA-abliterated-TIES-Qwen2.5-1.5B

Dumpling-Qwen2.5-1.5B-v2

nbeerbower/EVA-abliterated-TIES-Qwen2.5-1.5B finetuned on:

Method

QLoRA ORPO tune with 2x RTX 3090 for 2 epochs.

# QLoRA config
bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch_dtype,
    bnb_4bit_use_double_quant=True,
)

# LoRA config
peft_config = LoraConfig(
    r=64,
    lora_alpha=64,
    lora_dropout=0.05,
    bias="none",
    task_type="CAUSAL_LM",
    target_modules=['up_proj', 'down_proj', 'gate_proj', 'k_proj', 'q_proj', 'v_proj', 'o_proj']
)

# Training config
orpo_args = ORPOConfig(
    run_name=new_model,
    learning_rate=2e-5,
    lr_scheduler_type="linear",
    max_length=2048,
    max_prompt_length=1024,
    max_completion_length=1024,
    beta=0.1,
    per_device_train_batch_size=1,
    per_device_eval_batch_size=1,
    gradient_accumulation_steps=8,
    optim="paged_adamw_8bit",
    num_train_epochs=2,
    evaluation_strategy="steps",
    eval_steps=0.2,
    logging_steps=1,
    warmup_steps=10,
    max_grad_norm=10,
    report_to="wandb",
    output_dir="./results/",
    bf16=True,
)