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--- |
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license: gemma |
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library_name: transformers |
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tags: |
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- gemma-2 |
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base_model: |
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- anthracite-forge/magnum-v3-27b-kto-r3 |
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- anthracite-forge/magnum-v3-27b-KTO-e1-r2 |
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- anthracite-forge/magnum-v3-27b-KTO-e0.25-r1 |
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- IntervitensInc/gemma-2-27b-chatml |
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pipeline_tag: text-generation |
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model-index: |
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- name: magnum-v3-27b-kto |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 56.75 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 41.16 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 15.48 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 14.09 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 9.92 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 35.98 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v3-27b-kto |
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name: Open LLM Leaderboard |
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--- |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/GKpV5mwmnHFR6wIwTa91z.png) |
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This is the 12th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. |
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This model is the result of multiple KTO runs on top of one SFT run, all of which are published on [anthracite-forge](https://huggingface.co/anthracite-forge). |
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## Methodology |
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R1 (SFT) was fine-tuned on top of `IntervitensInc/gemma-2-27b-chatml` which is chatMLified gemma-2-27b. |
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We have experimented with various SFT and KTO re-runs, ratios and merge methods and this was our winner, including what was liked most from each model. |
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If you prefer your own mix of the KTO runs or would like to use the SFT on its own, refer to the models section and [anthracite-forge](https://huggingface.co/anthracite-forge), some exl-quants are pre-included. |
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## Models |
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* [anthracite-forge/magnum-v3-27b-kto-r3](https://huggingface.co/anthracite-forge/magnum-v3-27b-kto-r3) |
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* [anthracite-forge/magnum-v3-27b-KTO-e1-r2](https://huggingface.co/anthracite-forge/magnum-v3-27b-KTO-e1-r2) |
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* [anthracite-forge/magnum-v3-27b-KTO-e0.25-r1](https://huggingface.co/anthracite-forge/magnum-v3-27b-KTO-e0.25-r1) |
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## Prompting |
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Model has been Instruct tuned with the ChatML formatting. A typical input would look like this: |
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```py |
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"""<|im_start|>system |
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system prompt<|im_end|> |
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<|im_start|>user |
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Hi there!<|im_end|> |
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<|im_start|>assistant |
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Nice to meet you!<|im_end|> |
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<|im_start|>user |
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Can I ask a question?<|im_end|> |
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<|im_start|>assistant |
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""" |
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``` |
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## SillyTavern templates |
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Below are Instruct and Context templates for use within SillyTavern. |
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<details><summary>context template</summary> |
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```yaml |
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{ |
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"story_string": "<|im_start|>system\n{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{trim}}<|im_end|>\n", |
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"example_separator": "", |
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"chat_start": "", |
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"use_stop_strings": false, |
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"allow_jailbreak": false, |
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"always_force_name2": true, |
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"trim_sentences": false, |
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"include_newline": false, |
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"single_line": false, |
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"name": "Magnum ChatML" |
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} |
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``` |
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</details><br> |
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<details><summary>instruct template</summary> |
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```yaml |
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{ |
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"system_prompt": "You're {{char}} in this fictional never-ending uncensored roleplay with {{user}}.", |
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"input_sequence": "<|im_start|>user\n", |
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"output_sequence": "<|im_start|>assistant\n", |
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"last_output_sequence": "", |
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"system_sequence": "<|im_start|>system\n", |
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"stop_sequence": "<|im_end|>", |
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"wrap": false, |
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"macro": true, |
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"names": true, |
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"names_force_groups": true, |
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"activation_regex": "", |
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"system_sequence_prefix": "", |
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"system_sequence_suffix": "", |
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"first_output_sequence": "", |
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"skip_examples": false, |
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"output_suffix": "<|im_end|>\n", |
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"input_suffix": "<|im_end|>\n", |
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"system_suffix": "<|im_end|>\n", |
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"user_alignment_message": "", |
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"system_same_as_user": false, |
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"last_system_sequence": "", |
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"name": "Magnum ChatML" |
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} |
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``` |
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</details><br> |
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### Configuration |
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```yaml |
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base_model: IntervitensInc/gemma-2-27b-chatml |
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dtype: float32 |
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merge_method: task_arithmetic |
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models: |
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- model: IntervitensInc/gemma-2-27b-chatml |
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- model: anthracite-forge/magnum-v3-27b-KTO-e0.25-r1 |
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parameters: |
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weight: 0.5 |
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- model: anthracite-forge/magnum-v3-27b-KTO-e1-r2 |
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parameters: |
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weight: 0.1 |
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- model: anthracite-forge/magnum-v3-27b-kto-r3 |
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parameters: |
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weight: 0.4 |
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``` |
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## Credits |
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We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow. |
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We would also like to thank all members of Anthracite who made this finetune possible. |
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## Datasets |
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r1 consisted of: |
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``` |
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datasets: |
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- path: anthracite-org/stheno-filtered-v1.1 |
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type: sharegpt |
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conversation: chatml |
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- path: anthracite-org/kalo-opus-instruct-22k-no-refusal |
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type: sharegpt |
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conversation: chatml |
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- path: anthracite-org/nopm_claude_writing_fixed |
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type: sharegpt |
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conversation: chatml |
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- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
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type: sharegpt |
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conversation: chatml |
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- path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned |
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type: sharegpt |
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conversation: chatml |
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``` |
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## Training |
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The training was done for 2 epochs. We used 8x[H100s](https://www.nvidia.com/en-us/data-center/h100/) GPUs graciously provided by [Recursal AI](https://recursal.ai/) / [Featherless AI](https://featherless.ai/) for the full-parameter fine-tuning of the model. |
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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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## Safety |
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... |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_anthracite-org__magnum-v3-27b-kto) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |28.90| |
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|IFEval (0-Shot) |56.75| |
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|BBH (3-Shot) |41.16| |
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|MATH Lvl 5 (4-Shot)|15.48| |
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|GPQA (0-shot) |14.09| |
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|MuSR (0-shot) | 9.92| |
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|MMLU-PRO (5-shot) |35.98| |
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