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--- |
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license: apache-2.0 |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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- juanako |
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- mistral |
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- UNA |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: juanako-7b-UNA |
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results: |
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- task: |
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type: text-generation |
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name: TruthfulQA (MC2) |
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dataset: |
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type: text-generation |
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name: truthful_qa |
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config: multiple_choice |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 65.49 |
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- task: |
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type: text-generation |
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name: ARC-Challenge |
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dataset: |
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type: text-generation |
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name: ai2_arc |
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config: ARC-Challenge |
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split: test |
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metrics: |
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- type: accuracy |
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value: 68.09 |
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- task: |
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type: text-generation |
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name: HellaSwag |
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dataset: |
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type: text-generation |
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name: Rowan/hellaswag |
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split: test |
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metrics: |
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- type: accuracy |
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value: 85.20 |
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- task: |
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type: text-generation |
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name: GSM8k |
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dataset: |
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type: text-generation |
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name: gsm8k |
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config: main |
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split: test |
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metrics: |
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- type: accuracy |
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value: 48.98 |
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- task: |
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type: text-generation |
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name: Winogrande |
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dataset: |
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type: text-generation |
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name: winogrande |
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config: winogrande_debiased |
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split: test |
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metrics: |
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- type: accuracy |
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value: 76.8 |
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- task: |
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type: text-generation |
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name: MMLU |
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dataset: |
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type: text-generation |
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name: cais/mmlu |
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config: all |
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split: test |
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metrics: |
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- type: accuracy |
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value: 61.37 |
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- task: |
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type: text-generation |
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name: PiQA |
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dataset: |
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type: text-generation |
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name: piqa |
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split: test |
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metrics: |
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- type: accuracy |
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value: 83.57 |
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- task: |
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type: text-generation |
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name: DROP |
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dataset: |
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type: text-generation |
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name: drop |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 49.8 |
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- task: |
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type: text-generation |
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name: PubMedQA |
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dataset: |
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type: text-generation |
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name: bigbio/pubmed_qa |
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config: pubmed_qa_artificial_bigbio_qa |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 76.0 |
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--- |
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# juanako-7b-UNA-v2 |
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This model is a fine-tuned version of [fblgit/juanako-7b-UNA-v2-phase-1](https://huggingface.co./fblgit/juanako-7b-UNA-v2-phase-1) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It outperforms in many aspects most of the current Mistral based models. |
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Author [Xavier M.](mailto:[email protected]) @fblgit |
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## Scoring and records (26-November-2023) |
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Here are some results: |
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* Scores #1 7B Model |
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* Scores #4 GSM8k |
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* Scores #2 in TruthfulQA |
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* Scores #6 in CoPa |
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* Scores #2 in PiQA |
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* Scores #9 in BoolQ |
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Many evaluations were performed, but it behaves very balanced in multiple fields. Feel free to submit more evaluation results. |
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It scores: **65.1** according HuggingFace LLM Leaderboard. |
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|
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## Model description |
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juanako uses UNA, Uniform Neural Alignment. A training technique that ease alignment between transformer layers yet to be published. |
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## TruthfulQA 0-Shot |
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``` |
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| Tasks |Version|Filter|Metric|Value | |Stderr| |
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|--------------|-------|------|------|-----:|---|-----:| |
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|truthfulqa_mc2|Yaml |none |acc |0.6549|± |0.0153| |
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``` |
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## ARC 25-Shot |
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``` |
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| Tasks |Version|Filter| Metric |Value | |Stderr| |
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|-------------|-------|------|--------|-----:|---|-----:| |
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|arc_challenge|Yaml |none |acc |0.6476|± |0.0140| |
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| | |none |acc_norm|0.6809|± |0.0136| |
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``` |
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## HellaSwag 10-Shot |
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``` |
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| Tasks |Version|Filter| Metric |Value | |Stderr| |
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|---------|-------|------|--------|-----:|---|-----:| |
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|hellaswag|Yaml |none |acc |0.6703|± |0.0047| |
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| | |none |acc_norm|0.8520|± |0.0035| |
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``` |
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## GSM8k 5-Shot |
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``` |
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|Tasks|Version| Filter | Metric |Value | |Stderr| |
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|-----|-------|----------|-----------|-----:|---|-----:| |
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|gsm8k|Yaml |get-answer|exact_match|0.4898|± |0.0138| |
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``` |
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## GPT Evaluations 0-Shot |
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``` |
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| Tasks |Version|Filter| Metric |Value | |Stderr| |
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|--------------|-------|------|----------|-----:|---|-----:| |
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|boolq |Yaml |none |acc |0.8703|± |0.0059| |
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|lambada_openai|Yaml |none |perplexity|3.2598|± |0.0705| |
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| | |none |acc |0.7336|± |0.0062| |
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|piqa |Yaml |none |acc |0.8254|± |0.0089| |
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| | |none |acc_norm |0.8292|± |0.0088| |
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|sciq |Yaml |none |acc |0.9580|± |0.0063| |
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| | |none |acc_norm |0.9130|± |0.0089| |
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``` |
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## MathQA 0-Shot |
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``` |
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|Tasks |Version|Filter| Metric |Value | |Stderr| |
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|------|-------|------|--------|-----:|---|-----:| |
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|mathqa|Yaml |none |acc |0.3752|± |0.0089| |
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| | |none |acc_norm|0.3772|± |0.0089| |
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``` |
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## PiQa 1-Shot |
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``` |
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|Tasks|Version|Filter| Metric |Value | |Stderr| |
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|-----|-------|------|--------|-----:|---|-----:| |
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|piqa |Yaml |none |acc |0.8308|± |0.0087| |
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| | |none |acc_norm|0.8357|± |0.0086| |
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``` |
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## Winogrande 5-Shot |
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``` |
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| Tasks |Version|Filter|Metric|Value| |Stderr| |
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|----------|-------|------|------|----:|---|-----:| |
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|winogrande|Yaml |none |acc |0.768|± |0.0119| |
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``` |
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## PubMedQA 0-Shot |
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``` |
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| Tasks |Version|Filter|Metric|Value| |Stderr| |
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|--------|-------|------|------|----:|---|-----:| |
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|pubmedqa|Yaml |none |acc | 0.76|± |0.0191| |
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``` |
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## RACE 1-Shot |
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``` |
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|Tasks|Version|Filter|Metric|Value | |Stderr| |
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|-----|-------|------|------|-----:|---|-----:| |
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|race |Yaml |none |acc |0.5282|± |0.0154| |
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``` |
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## MMLU 5-Shot (8-Bit) |
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``` |
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| Groups |Version|Filter|Metric|Value | |Stderr| |
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|------------------|-------|------|------|-----:|---|-----:| |
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|mmlu |N/A |none |acc |0.6137|± |0.1243| |
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| - humanities |N/A |none |acc |0.5671|± |0.1101| |
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| - other |N/A |none |acc |0.6859|± |0.1164| |
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| - social_sciences|N/A |none |acc |0.7195|± |0.0713| |
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| - stem |N/A |none |acc |0.5087|± |0.1297| |
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``` |
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## DROP 3-Shot (8-Bit) (Instruct-Eval) |
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``` |
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{'score': 0.49801113762927607} |
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{'drop': 49.8} |
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drop: 49.8 |
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``` |
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|
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## CRASS 0-Shot (Instruct-Eval) |
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``` |
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{'score': 0.8357664233576643} |
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{'crass': 83.58} |
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crass: 83.58 |
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``` |
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### Training hyperparameters |
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|
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 14 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 224 |
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- total_eval_batch_size: 14 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 1 |
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|
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### Training results |
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|
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.4795 | 0.2 | 56 | 0.4958 | -1.3684 | -2.6385 | 0.7552 | 1.2701 | -265.3887 | -241.2612 | -2.2572 | -2.4922 | |
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| 0.4642 | 0.4 | 112 | 0.4859 | -1.0380 | -1.9769 | 0.7273 | 0.9389 | -258.7718 | -237.9569 | -2.2414 | -2.4751 | |
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| 0.4758 | 0.61 | 168 | 0.4808 | -1.2594 | -2.3704 | 0.7343 | 1.1110 | -262.7074 | -240.1708 | -2.2305 | -2.4633 | |
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| 0.4549 | 0.81 | 224 | 0.4768 | -1.1906 | -2.3201 | 0.7552 | 1.1295 | -262.2044 | -239.4827 | -2.2284 | -2.4610 | |
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### Framework versions |
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|
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- Transformers 4.35.0-UNA |
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- Pytorch 2.1.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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|
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## Citations |
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If you find juanako useful please: |
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``` |
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@misc{juanako7buna, |
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title={Juanako: Uniform Neural Alignment}, |
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author={Xavier Murias}, |
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year={2023}, |
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publisher = {HuggingFace}, |
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journal = {HuggingFace repository}, |
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howpublished = {\url{https://huggingface.co./fblgit/juanako-7b-UNA}}, |
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} |
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``` |
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|
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``` |
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@misc{lin2021truthfulqa, |
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title={TruthfulQA: Measuring How Models Mimic Human Falsehoods}, |
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author={Stephanie Lin and Jacob Hilton and Owain Evans}, |
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year={2021}, |
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eprint={2109.07958}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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@misc{tunstall2023zephyr, |
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title={Zephyr: Direct Distillation of LM Alignment}, |
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author={Lewis Tunstall and Edward Beeching and Nathan Lambert and Nazneen Rajani and Kashif Rasul and Younes Belkada and Shengyi Huang and Leandro von Werra and Clémentine Fourrier and Nathan Habib and Nathan Sarrazin and Omar Sanseviero and Alexander M. Rush and Thomas Wolf}, |
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year={2023}, |
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eprint={2310.16944}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG} |
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} |
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@article{cobbe2021gsm8k, |
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title={Training Verifiers to Solve Math Word Problems}, |
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author={Cobbe, Karl and Kosaraju, Vineet and Bavarian, Mohammad and Chen, Mark and Jun, Heewoo and Kaiser, Lukasz and Plappert, Matthias and Tworek, Jerry and Hilton, Jacob and Nakano, Reiichiro and Hesse, Christopher and Schulman, John}, |
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journal={arXiv preprint arXiv:2110.14168}, |
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year={2021} |
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} |
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@inproceedings{Bisk2020, |
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author = {Yonatan Bisk and Rowan Zellers and |
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Ronan Le Bras and Jianfeng Gao |
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and Yejin Choi}, |
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title = {PIQA: Reasoning about Physical Commonsense in |
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Natural Language}, |
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booktitle = {Thirty-Fourth AAAI Conference on |
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Artificial Intelligence}, |
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year = {2020}, |
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} |
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@software{eval-harness, |
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author = {Gao, Leo and |
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Tow, Jonathan and |
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Biderman, Stella and |
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Black, Sid and |
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DiPofi, Anthony and |
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Foster, Charles and |
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Golding, Laurence and |
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Hsu, Jeffrey and |
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McDonell, Kyle and |
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Muennighoff, Niklas and |
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Phang, Jason and |
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Reynolds, Laria and |
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Tang, Eric and |
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Thite, Anish and |
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Wang, Ben and |
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Wang, Kevin and |
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Zou, Andy}, |
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title = {A framework for few-shot language model evaluation}, |
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month = sep, |
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year = 2021, |
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publisher = {Zenodo}, |
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version = {v0.0.1}, |
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doi = {10.5281/zenodo.5371628}, |
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url = {https://doi.org/10.5281/zenodo.5371628} |
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} |
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@misc{rafailov2023direct, |
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title={Direct Preference Optimization: Your Language Model is Secretly a Reward Model}, |
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author={Rafael Rafailov and Archit Sharma and Eric Mitchell and Stefano Ermon and Christopher D. Manning and Chelsea Finn}, |
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year={2023}, |
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eprint={2305.18290}, |
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archivePrefix={arXiv}, |
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} |
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``` |
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