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--- |
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library_name: peft |
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base_model: NousResearch/Meta-Llama-3-70B-Instruct |
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license: apache-2.0 |
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--- |
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# Model Card for radm/Llama-3-70B-Instruct-AH-AWQ |
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<!-- Provide a quick summary of what the model is/does. --> |
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This model fine-tuned to be a judge on Arena Hard (https://github.com/lm-sys/arena-hard-auto). |
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The base model was trained using LoRA, combined with an adapter and converted to AWQ format. |
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Only LoRA adapter for base model can be found here (https://huggingface.co/radm/Llama-3-70B-Instruct-AH-lora) |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** [radm] |
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- **Model type:** [Llama-3-70b] |
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- **Language(s) (NLP):** [English] |
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- **License:** [apache-2.0] |
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- **Finetuned from model [optional]:** [NousResearch/Meta-Llama-3-70B-Instruct] |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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Use repository (https://github.com/r4dm/arena-hard-local) for evaluate with local judge model. |
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### Results |
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#### Llama-3-70B-Instruct-GPTQ as judge: |
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```console |
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Llama-3-Instruct-8B-SimPO | score: 78.3 | 95% CI: (-1.5, 1.2) | average #tokens: 545 |
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SELM-Llama-3-8B-Instruct-iter-3 | score: 72.8 | 95% CI: (-2.1, 1.4) | average #tokens: 606 |
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Meta-Llama-3-8B-Instruct-f16 | score: 65.3 | 95% CI: (-1.8, 2.1) | average #tokens: 560 |
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suzume-llama-3-8B-multilingual-orpo-borda-half | score: 63.5 | 95% CI: (-1.6, 2.1) | average #tokens: 978 |
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Phi-3-medium-128k-instruct | score: 50.0 | 95% CI: (0.0, 0.0) | average #tokens: 801 |
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suzume-llama-3-8B-multilingual | score: 48.1 | 95% CI: (-2.2, 1.8) | average #tokens: 767 |
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aya-23-8B | score: 48.0 | 95% CI: (-2.0, 2.1) | average #tokens: 834 |
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Vikhr-7B-instruct_0.5 | score: 19.6 | 95% CI: (-1.3, 1.5) | average #tokens: 794 |
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alpindale_gemma-2b-it | score: 11.2 | 95% CI: (-1.0, 0.8) | average #tokens: 425 |
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``` |
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#### Llama-3-70B-Instruct-AH-AWQ as judge: |
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```console |
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Llama-3-Instruct-8B-SimPO | score: 83.8 | 95% CI: (-1.4, 1.3) | average #tokens: 545 |
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SELM-Llama-3-8B-Instruct-iter-3 | score: 78.8 | 95% CI: (-1.7, 1.9) | average #tokens: 606 |
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suzume-llama-3-8B-multilingual-orpo-borda-half | score: 71.8 | 95% CI: (-1.7, 2.4) | average #tokens: 978 |
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Meta-Llama-3-8B-Instruct-f16 | score: 69.8 | 95% CI: (-1.9, 1.7) | average #tokens: 560 |
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suzume-llama-3-8B-multilingual | score: 54.0 | 95% CI: (-2.1, 2.1) | average #tokens: 767 |
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aya-23-8B | score: 50.4 | 95% CI: (-1.7, 1.7) | average #tokens: 834 |
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Phi-3-medium-128k-instruct | score: 50.0 | 95% CI: (0.0, 0.0) | average #tokens: 801 |
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Vikhr-7B-instruct_0.5 | score: 14.2 | 95% CI: (-1.3, 1.0) | average #tokens: 794 |
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alpindale_gemma-2b-it | score: 7.9 | 95% CI: (-0.9, 0.8) | average #tokens: 425 |
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``` |
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## Training Details |
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### Training Data |
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<!-- 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. --> |
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Datasets: |
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- radm/arenahard_gpt4vsllama3 |
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- radm/truthy-dpo-v0.1-ru |
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- jondurbin/truthy-dpo-v0.1 |
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#### Training Hyperparameters |
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- **Training regime:** [bf16] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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- **Load in 4 bit:** [True] |
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- **Target modules:** [all] |
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- **LoRA rank:** [16] |
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- **Max seq length:** [8192] |
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- **Use gradient checkpointing:** [unsloth] |
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- **trainer:** [ORPOTrainer] |
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- **Batch size:** [1] |
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- **Gradient accumulation steps:** [4] |
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- **Epochs:** [1] |
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### Hardware |
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- **Hardware Type:** [Nvidia A100 80 gb] |
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- **Hours used:** [11 hours] |
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### Framework versions |
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- PEFT 0.10.0 |
