README.md

---
library_name: peft
base_model: NousResearch/Meta-Llama-3-70B-Instruct
license: apache-2.0
---

# Model Card for radm/Llama-3-70B-Instruct-AH-AWQ

<!-- Provide a quick summary of what the model is/does. -->
This model fine-tuned to be a judge on Arena Hard (https://github.com/lm-sys/arena-hard-auto).
The base model was trained using LoRA, combined with an adapter and converted to AWQ format.

Only LoRA adapter for base model can be found here (https://huggingface.co/radm/Llama-3-70B-Instruct-AH-lora)

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [radm]
- **Model type:** [Llama-3-70b]
- **Language(s) (NLP):** [English]
- **License:** [apache-2.0]
- **Finetuned from model [optional]:** [NousResearch/Meta-Llama-3-70B-Instruct]

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
[More Information Needed]

## Training Details

### Training Data

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Datasets:
- radm/arenahard_gpt4vsllama3
- radm/truthy-dpo-v0.1-ru
- jondurbin/truthy-dpo-v0.1

#### Training Hyperparameters

- **Training regime:** [bf16] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
- **Load in 4 bit:** [True]
- **Target modules:** [all]
- **LoRA rank:** [16]
- **Max seq length:** [8192]
- **Use gradient checkpointing:** [unsloth]
- **trainer:** [ORPOTrainer]
- **Batch size:** [1]
- **Gradient accumulation steps:** [4]
- **Epochs:** [1]

### Results

[More Information Needed]

## Hardware

- **Hardware Type:** [Nvidia A100 80 gb]
- **Hours used:** [11 hours]

### Framework versions

- PEFT 0.10.0