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--- |
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language: |
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- en |
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license: other |
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library_name: transformers |
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tags: |
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- chat |
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license_name: mrl |
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pipeline_tag: text-generation |
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model-index: |
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- name: magnum-v4-22b |
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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: 56.29 |
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name: strict accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b |
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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: 35.55 |
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name: normalized accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b |
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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: 17.6 |
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name: exact match |
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source: |
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url: >- |
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b |
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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: 10.4 |
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name: acc_norm |
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source: |
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url: >- |
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b |
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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: 13.43 |
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name: acc_norm |
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source: |
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url: >- |
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b |
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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: 31.44 |
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name: accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b |
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name: Open LLM Leaderboard |
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datasets: |
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- anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system |
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- anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system |
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- anthracite-org/kalo-opus-instruct-3k-filtered-no-system |
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- anthracite-org/nopm_claude_writing_fixed |
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- anthracite-org/kalo_opus_misc_240827_no_system |
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- anthracite-org/kalo_misc_part2_no_system |
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--- |
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This is 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 fine-tuned on top of [Mistral-Small-Instruct-2409](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409). |
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## Prompting |
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A typical input would look like this: |
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```py |
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<s>[INST] SYSTEM MESSAGE |
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USER MESSAGE[/INST] ASSISTANT MESSAGE</s>[INST] USER MESSAGE[/INST] |
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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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default SillyTavern template works fine |
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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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default SillyTavern template works fine |
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``` |
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</details><br> |
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## Axolotl config |
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<details><summary>See axolotl config</summary> |
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```yaml |
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base_model: /workspace/models/Mistral-Small-Instruct-2409 |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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hub_model_id: anthracite-org/magnum-v4-22b-r4 |
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hub_strategy: "all_checkpoints" |
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push_dataset_to_hub: |
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hf_use_auth_token: true |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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#liger_cross_entropy: true |
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liger_fused_linear_cross_entropy: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system |
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type: custommistralv2v3 |
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- path: anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system |
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type: custommistralv2v3 |
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- path: anthracite-org/kalo-opus-instruct-3k-filtered-no-system |
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type: custommistralv2v3 |
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- path: anthracite-org/nopm_claude_writing_fixed |
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type: custommistralv2v3 |
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- path: anthracite-org/kalo_opus_misc_240827_no_system |
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type: custommistralv2v3 |
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- path: anthracite-org/kalo_misc_part2_no_system |
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type: custommistralv2v3 |
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#chat_template: mistral_v2v3 |
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shuffle_merged_datasets: true |
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#default_system_message: "You are an assistant that responds to the user." |
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dataset_prepared_path: /workspace/data/magnum-22b-data |
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val_set_size: 0.0 |
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output_dir: /workspace/data/22b-r4-fft-out |
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sequence_len: 32768 |
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sample_packing: true |
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pad_to_sequence_len: true |
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adapter: |
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lora_model_dir: |
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lora_r: |
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lora_alpha: |
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lora_dropout: |
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lora_target_linear: |
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lora_fan_in_fan_out: |
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wandb_project: 22b-magnum-fft |
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wandb_entity: |
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wandb_watch: |
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wandb_name: v4-r4-attempt-01 |
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wandb_log_model: |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 1 |
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num_epochs: 2 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000004 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 40 |
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evals_per_epoch: |
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eval_table_size: |
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eval_max_new_tokens: |
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saves_per_epoch: 2 |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.1 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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``` |
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</details><br> |
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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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- [anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system](https://huggingface.co/datasets/anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system) |
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- [anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system) |
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- [anthracite-org/kalo-opus-instruct-3k-filtered-no-system](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-3k-filtered-no-system) |
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- [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed) |
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- [anthracite-org/kalo_opus_misc_240827_no_system](https://huggingface.co/datasets/anthracite-org/kalo_opus_misc_240827_no_system) |
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- [anthracite-org/kalo_misc_part2_no_system](https://huggingface.co/datasets/anthracite-org/kalo_misc_part2_no_system) |
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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-v4-22b) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |27.45| |
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|IFEval (0-Shot) |56.29| |
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|BBH (3-Shot) |35.55| |
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|MATH Lvl 5 (4-Shot)|17.60| |
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|GPQA (0-shot) |10.40| |
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|MuSR (0-shot) |13.43| |
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|MMLU-PRO (5-shot) |31.44| |
