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--- |
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library_name: transformers |
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license: apache-2.0 |
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datasets: |
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- Locutusque/hercules-v2.0 |
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- CollectiveCognition/chats-data-2023-09-22 |
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language: |
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- en |
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--- |
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# lr-experiment1-7B |
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The lr-experiment model series is a research project I'm conducting that I will be using to determine the best learning rate to use while fine-tuning Mistral. This model uses a learning rate of 2e-5 with a cosine scheduler and no warmup steps. |
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I used Locutusque/Hercules-2.0-Mistral-7B as a base model, and further fine-tuned it on CollectiveCognition/chats-data-2023-09-22 using QLoRA for 3 epochs. I will be keeping track of evaluation results, and will comparing it to upcoming models. |
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# Evals |
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr| |
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|---------------------------------|-------|------|------|--------|-----:|---|-----:| |
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|agieval_nous |N/A |none |None |acc |0.3645|± |0.0093| |
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| | |none |None |acc_norm|0.3468|± |0.0092| |
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| - agieval_aqua_rat | 1|none |None |acc |0.2283|± |0.0264| |
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| | |none |None |acc_norm|0.2283|± |0.0264| |
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| - agieval_logiqa_en | 1|none |None |acc |0.2965|± |0.0179| |
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| | |none |None |acc_norm|0.3303|± |0.0184| |
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| - agieval_lsat_ar | 1|none |None |acc |0.2217|± |0.0275| |
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| | |none |None |acc_norm|0.1783|± |0.0253| |
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| - agieval_lsat_lr | 1|none |None |acc |0.4039|± |0.0217| |
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| | |none |None |acc_norm|0.3686|± |0.0214| |
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| - agieval_lsat_rc | 1|none |None |acc |0.4870|± |0.0305| |
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| | |none |None |acc_norm|0.4424|± |0.0303| |
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| - agieval_sat_en | 1|none |None |acc |0.6408|± |0.0335| |
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| | |none |None |acc_norm|0.5971|± |0.0343| |
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| - agieval_sat_en_without_passage| 1|none |None |acc |0.3932|± |0.0341| |
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| | |none |None |acc_norm|0.3835|± |0.0340| |
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| - agieval_sat_math | 1|none |None |acc |0.3455|± |0.0321| |
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| | |none |None |acc_norm|0.2727|± |0.0301| |
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| Groups |Version|Filter|n-shot| Metric |Value | |Stderr| |
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|------------|-------|------|------|--------|-----:|---|-----:| |
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|agieval_nous|N/A |none |None |acc |0.3645|± |0.0093| |
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| | |none |None |acc_norm|0.3468|± |0.0092| |
