--- license: llama3 tags: - axolotl - dpo - trl - generated_from_trainer base_model: meta-llama/Meta-Llama-3-8B-Instruct datasets: - HumanLLMs/humanish-dpo-project model-index: - name: Humanish-LLama3.1-8B-Instruct results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 64.98 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 28.01 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 8.46 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 0.78 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 2.0 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 30.02 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct name: Open LLM Leaderboard --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml base_model: meta-llama/Meta-Llama-3-8B-Instruct model_type: LlamaForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: true load_in_4bit: false strict: false chat_template: llama3 rl: dpo datasets: - path: HumanLLMs/humanish-dpo-project type: llama3.prompt_pairs chat_template: llama3 dataset_prepared_path: val_set_size: 0.05 output_dir: ./humanish-llama3-8b-instruct sequence_len: 8192 sample_packing: false pad_to_sequence_len: true adapter: lora lora_model_dir: lora_r: 8 lora_alpha: 4 lora_dropout: 0.05 lora_target_linear: true lora_fan_in_fan_out: wandb_project: Humanish-DPO wandb_entity: wandb_watch: wandb_name: wandb_log_model: hub_model_id: HumanLLMs/Humanish-LLama3.1-8B-Instruct gradient_accumulation_steps: 8 micro_batch_size: 2 num_epochs: 1 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true s2_attention: warmup_steps: 10 evals_per_epoch: 2 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 1 debug: deepspeed: weight_decay: 0.0 fsdp: fsdp_config: save_safetensors: true ```

# Humanish-LLama3.1-8B-Instruct This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 341 ### Training results ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.20.0 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_HumanLLMs__Humanish-LLama3.1-8B-Instruct) | Metric |Value| |-------------------|----:| |Avg. |22.38| |IFEval (0-Shot) |64.98| |BBH (3-Shot) |28.01| |MATH Lvl 5 (4-Shot)| 8.46| |GPQA (0-shot) | 0.78| |MuSR (0-shot) | 2.00| |MMLU-PRO (5-shot) |30.02|