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AlphaMonarch-dora

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
+license: cc-by-nc-4.0
+base_model: mlabonne/NeuralMonarch-7B
+tags:
+- generated_from_trainer
+- mistral
+- instruct
+- finetune
+- chatml
+- gpt4
+- synthetic data
+- distillation
+model-index:
+- name: AlphaMonarch-dora
+  results: []
+datasets:
+- argilla/OpenHermes2.5-dpo-binarized-alpha
+language:
+- en
 library_name: transformers
+pipeline_tag: text-generation
 ---
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64fc6d81d75293f417fee1d1/7xlnpalOC4qtu-VABsib4.jpeg)
+# AlphaMonarch-dora
+<!-- Provide a quick summary of what the model is/does. -->
+AlphaMonarch-laser is a DPO fine-tuned of [mlabonne/NeuralMonarch-7B](https://huggingface.co/mlabonne/NeuralMonarch-7B/) using the [argilla/OpenHermes2.5-dpo-binarized-alpha](https://huggingface.co/datasets/argilla/OpenHermes2.5-dpo-binarized-alpha) preference dataset using DoRA...
+## 🏆 Evaluation results
+# Nous Benchmark
+### AGIEVAL
+| Task                           | Version | Accuracy | Accuracy StdErr | Normalized Accuracy | Normalized Accuracy StdErr |
+|--------------------------------|---------|----------|-----------------|---------------------|-----------------------------|
+| agieval_aqua_rat               | 0       | 28.35%   | 2.83%           | 26.38%              | 2.77%                       |
+| agieval_logiqa_en              | 0       | 38.71%   | 1.91%           | 38.25%              | 1.90%                       |
+| agieval_lsat_ar                | 0       | 23.91%   | 2.82%           | 23.48%              | 2.80%                       |
+| agieval_lsat_lr                | 0       | 52.55%   | 2.21%           | 53.73%              | 2.21%                       |
+| agieval_lsat_rc                | 0       | 66.91%   | 2.87%           | 66.54%              | 2.88%                       |
+| agieval_sat_en                 | 0       | 78.64%   | 2.86%           | 78.64%              | 2.86%                       |
+| agieval_sat_en_without_passage | 0       | 45.15%   | 3.48%           | 44.17%              | 3.47%                       |
+| agieval_sat_math               | 0       | 33.64%   | 3.19%           | 31.82%              | 3.15%                       |
+AVG = 45.976
+### GPT4ALL
+| Task         | Version | Accuracy | Accuracy StdErr | Normalized Accuracy | Normalized Accuracy StdErr |
+|--------------|---------|----------|-----------------|---------------------|-----------------------------|
+| arc_challenge| 0       | 65.87%   | 1.39%           | 67.92%              | 1.36%                       |
+| arc_easy     | 0       | 86.49%   | 0.70%           | 80.64%              | 0.81%                       |
+| boolq        | 1       | 87.16%   | 0.59%           | -                   | -                           |
+| hellaswag    | 0       | 69.86%   | 0.46%           | 87.51%              | 0.33%                       |
+| openbookqa   | 0       | 39.00%   | 2.18%           | 49.20%              | 2.24%                       |
+| piqa         | 0       | 83.03%   | 0.88%           | 84.82%              | 0.84%                       |
+| winogrande   | 0       | 80.98%   | 1.10%           | -                   | -                           |
+AVG = 73.18
+### TRUTHFUL-QA
+| Task          | Version | MC1 Accuracy | MC1 Accuracy StdErr | MC2 Accuracy | MC2 Accuracy StdErr |
+|---------------|---------|--------------|---------------------|--------------|---------------------|
+| truthfulqa_mc | 1       | 62.91%       | 1.69%               | 78.48%       | 1.37%               |
+VG = 70.69
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-7
+- train_batch_size: 2
+- eval_batch_size: Not specified
+- seed: Not specified
+- gradient_accumulation_steps: 8
+- total_train_batch_size: Not specified
+- optimizer: PagedAdamW with 32-bit precision
+- lr_scheduler_type: Cosine
+- lr_scheduler_warmup_steps: 100
+- training_steps: 1080
+### Framework versions
+- Transformers 4.39.0.dev0
+- Peft 0.9.1.dev0
+- Datasets 2.18.0
+- torch 2.2.0
+- accelerate 0.27.2