|
--- |
|
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. --> |
|
Use repository (https://github.com/r4dm/arena-hard-local) for evaluate with local judge model. |
|
|
|
## Results |
|
|
|
#### Llama-3-70B-Instruct-GPTQ as judge: |
|
```console |
|
Llama-3-Instruct-8B-SimPO | score: 78.3 | 95% CI: (-1.5, 1.2) | average #tokens: 545 |
|
SELM-Llama-3-8B-Instruct-iter-3 | score: 72.8 | 95% CI: (-2.1, 1.4) | average #tokens: 606 |
|
Meta-Llama-3-8B-Instruct-f16 | score: 65.3 | 95% CI: (-1.8, 2.1) | average #tokens: 560 |
|
suzume-llama-3-8B-multilingual-orpo-borda-half | score: 63.5 | 95% CI: (-1.6, 2.1) | average #tokens: 978 |
|
Phi-3-medium-128k-instruct | score: 50.0 | 95% CI: (0.0, 0.0) | average #tokens: 801 |
|
suzume-llama-3-8B-multilingual | score: 48.1 | 95% CI: (-2.2, 1.8) | average #tokens: 767 |
|
aya-23-8B | score: 48.0 | 95% CI: (-2.0, 2.1) | average #tokens: 834 |
|
Vikhr-7B-instruct_0.5 | score: 19.6 | 95% CI: (-1.3, 1.5) | average #tokens: 794 |
|
alpindale_gemma-2b-it | score: 11.2 | 95% CI: (-1.0, 0.8) | average #tokens: 425 |
|
``` |
|
#### Llama-3-70B-Instruct-AH-AWQ as judge: |
|
```console |
|
Llama-3-Instruct-8B-SimPO | score: 83.8 | 95% CI: (-1.4, 1.3) | average #tokens: 545 |
|
SELM-Llama-3-8B-Instruct-iter-3 | score: 78.8 | 95% CI: (-1.7, 1.9) | average #tokens: 606 |
|
suzume-llama-3-8B-multilingual-orpo-borda-half | score: 71.8 | 95% CI: (-1.7, 2.4) | average #tokens: 978 |
|
Meta-Llama-3-8B-Instruct-f16 | score: 69.8 | 95% CI: (-1.9, 1.7) | average #tokens: 560 |
|
suzume-llama-3-8B-multilingual | score: 54.0 | 95% CI: (-2.1, 2.1) | average #tokens: 767 |
|
aya-23-8B | score: 50.4 | 95% CI: (-1.7, 1.7) | average #tokens: 834 |
|
Phi-3-medium-128k-instruct | score: 50.0 | 95% CI: (0.0, 0.0) | average #tokens: 801 |
|
Vikhr-7B-instruct_0.5 | score: 14.2 | 95% CI: (-1.3, 1.0) | average #tokens: 794 |
|
alpindale_gemma-2b-it | score: 7.9 | 95% CI: (-0.9, 0.8) | average #tokens: 425 |
|
``` |
|
|
|
## 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] |
|
|
|
### Hardware |
|
|
|
- **Hardware Type:** [Nvidia A100 80 gb] |
|
- **Hours used:** [11 hours] |
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
