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---
library_name: peft
base_model: NousResearch/Meta-Llama-3-70B-Instruct
license: apache-2.0
---
# Model Card for radm/Llama-3-70B-Instruct-AH-lora
<!-- Provide a quick summary of what the model is/does. -->
This is a LORA adapter for NousResearch/Meta-Llama-3-70B-Instruct, fine-tuned to be a judge on Arena Hard (https://github.com/lm-sys/arena-hard-auto)
## 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
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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 |