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README.md
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@@ -28,32 +28,8 @@ Only LoRA adapter for base model can be found here (https://huggingface.co/radm/
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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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## 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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### 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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alpindale_gemma-2b-it | score: 7.9 | 95% CI: (-0.9, 0.8) | average #tokens: 425
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```
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##
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- **Hardware Type:** [Nvidia A100 80 gb]
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- **Hours used:** [11 hours]
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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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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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