---
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
---

![image/png](https://huggingface.co/nbeerbower/Dumpling-Qwen2.5-32B/resolve/main/dumpling_cover.png?download=true)

# Dumpling-Qwen2.5-1.5B-v2

[nbeerbower/EVA-abliterated-TIES-Qwen2.5-1.5B](https://huggingface.co/nbeerbower/EVA-abliterated-TIES-Qwen2.5-1.5B) finetuned on: 
* [nbeerbower/GreatFirewall-DPO](https://huggingface.co/datasets/nbeerbower/GreatFirewall-DPO)
* [nbeerbower/Schule-DPO](https://huggingface.co/datasets/nbeerbower/Schule-DPO)
* [nbeerbower/Purpura-DPO](https://huggingface.co/datasets/nbeerbower/Purpura-DPO)
* [nbeerbower/Arkhaios-DPO](https://huggingface.co/datasets/nbeerbower/Arkhaios-DPO)
* [jondurbin/truthy-dpo-v0.1](https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1)
* [antiven0m/physical-reasoning-dpo](https://huggingface.co/datasets/antiven0m/physical-reasoning-dpo)
* [flammenai/Date-DPO-NoAsterisks](https://huggingface.co/datasets/flammenai/Date-DPO-NoAsterisks)
* [flammenai/Prude-Phi3-DPO](https://huggingface.co/datasets/flammenai/Prude-Phi3-DPO)
* [Atsunori/HelpSteer2-DPO](https://huggingface.co/datasets/Atsunori/HelpSteer2-DPO) (1,000 samples)
* [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1)
* [nbeerbower/gutenberg2-dpo](https://huggingface.co/datasets/nbeerbower/gutenberg2-dpo)
* [nbeerbower/gutenberg-moderne-dpo](https://huggingface.co/datasets/nbeerbower/gutenberg-moderne-dpo).

### Method

[QLoRA ORPO tune](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) with 2x RTX 3090 for 2 epochs.

```python
# 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,
)
```