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--- |
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base_model: teknium/OpenHermes-2.5-Mistral-7B |
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license: apache-2.0 |
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datasets: |
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- teknium/openhermes |
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- argilla/ultrafeedback-binarized-preferences |
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- Intel/orca_dpo_pairs |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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--- |
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# DPOpenHermes 7B |
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## OpenHermes x Notus x Neural |
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This is an RL fine tuned [OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) using the [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) and [argilla/ultrafeedback-binarized-preferences](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences) preference datasets for reinforcement learning using Direct Preference Optimization (DPO) |
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DPOpenHermes is trained using qLoRA. The adapter is also provided in this model repo. |
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# Training Details |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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DPOpenHermes was trained on a single H100 80GB hosted on RunPod for ~10h for 0.6 epochs of the dataset. |
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https://wandb.ai/oaaic/openhermes-dpo/reports/DPOpenHermes--Vmlldzo2MTQ3NDg2 |
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# Benchmarks |
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## AGIEval |
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``` |
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| Task |Version| Metric |Value | |Stderr| |
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|------------------------------|------:|--------|-----:|---|-----:| |
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|agieval_aqua_rat | 0|acc |0.2480|_ |0.0272| |
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| | |acc_norm|0.2520|_ |0.0273| |
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|agieval_logiqa_en | 0|acc |0.3810|_ |0.0190| |
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| | |acc_norm|0.3856|_ |0.0191| |
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|agieval_lsat_ar | 0|acc |0.2348|_ |0.0280| |
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| | |acc_norm|0.2304|_ |0.0278| |
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|agieval_lsat_lr | 0|acc |0.5118|_ |0.0222| |
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| | |acc_norm|0.5196|_ |0.0221| |
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|agieval_lsat_rc | 0|acc |0.5948|_ |0.0300| |
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| | |acc_norm|0.5688|_ |0.0303| |
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|agieval_sat_en | 0|acc |0.7427|_ |0.0305| |
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| | |acc_norm|0.7427|_ |0.0305| |
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|agieval_sat_en_without_passage| 0|acc |0.4563|_ |0.0348| |
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| | |acc_norm|0.4515|_ |0.0348| |
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|agieval_sat_math | 0|acc |0.3818|_ |0.0328| |
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| | |acc_norm|0.3682|_ |0.0326| |
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``` |
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Average: 0.4399 |
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## GPT4All |
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``` |
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| Task |Version| Metric |Value | |Stderr| |
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|-------------|------:|--------|-----:|---|-----:| |
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|arc_challenge| 0|acc |0.5930|_ |0.0144| |
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| | |acc_norm|0.6323|_ |0.0141| |
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|arc_easy | 0|acc |0.8443|_ |0.0074| |
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| | |acc_norm|0.8295|_ |0.0077| |
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|boolq | 1|acc |0.8599|_ |0.0061| |
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|hellaswag | 0|acc |0.6548|_ |0.0047| |
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| | |acc_norm|0.8365|_ |0.0037| |
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|openbookqa | 0|acc |0.3520|_ |0.0214| |
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| | |acc_norm|0.4640|_ |0.0223| |
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|piqa | 0|acc |0.8210|_ |0.0089| |
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| | |acc_norm|0.8335|_ |0.0087| |
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|winogrande | 0|acc |0.7466|_ |0.0122| |
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``` |
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Average: 0.7431 |
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## TruthfulQA |
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``` |
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hf-causal-experimental (pretrained=openaccess-ai-collective/dpopenhermes-alpha-v1,dtype=bfloat16,trust_remote_code=True,use_accelerate=True), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16 |
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| Task |Version|Metric|Value | |Stderr| |
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|-------------|------:|------|-----:|---|-----:| |
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|truthfulqa_mc| 1|mc1 |0.4186|_ |0.0173| |
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| | |mc2 |0.5847|_ |0.0153| |
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``` |
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