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---
license: apache-2.0
library_name: transformers
base_model:
- nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated
datasets:
- nbeerbower/Schule-DPO
- nbeerbower/Arkhaios-DPO
- nbeerbower/Purpura-DPO
---
# mistral-nemo-kartoffel-12B
[Mahou-1.5-mistral-nemo-12B-lorablated](https://huggingface.co./nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated) finetuned on various datasets.
### Method
[ORPO tuned](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) with 8x A100 for 2 epochs.
QLoRA config:
```
# 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=16,
lora_alpha=32,
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=8e-6,
lr_scheduler_type="linear",
max_length=2048,
max_prompt_length=1024,
max_completion_length=1024,
beta=0.1,
per_device_train_batch_size=4,
per_device_eval_batch_size=4,
gradient_accumulation_steps=1,
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,
gradient_checkpointing=True,
)
```
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