# Orpo-Llama-3.2-1B-40k AdamLucek/Orpo-Llama-3.2-1B-40k is an [ORPO](https://arxiv.org/abs/2403.07691) fine tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on 1 epoch of [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k). Trained for 11 hours on an A100 GPU with [this training script](https://colab.research.google.com/drive/1kax8rsqtBhR7is6XNHgVkvtblz9Pmldi?usp=sharing) For full model details, refer to the base model page [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) ## Evaluations In comparsion to [AdamLucek/Orpo-Llama-3.2-1B-15k](https://huggingface.co/AdamLucek/Orpo-Llama-3.2-1B-15k) using [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness). | Benchmark | 15k Accuracy | 15k Normalized | 40k Accuracy | 40k Normalized | Notes | |----------------|--------------|----------------|--------------|----------------|-------------------------------------------| | AGIEval | 22.14% | 21.01% | 23.57% | 23.26% | 0-Shot Average across multiple reasoning tasks | | GPT4ALL | 51.15% | 54.38% | 51.63% | 55.00% | 0-Shot Average across all categories | | TruthfulQA | 42.79% | N/A | 42.14% | N/A | MC2 accuracy | | MMLU | 31.22% | N/A | 31.01% | N/A | 5-Shot Average across all categories | | Winogrande | 61.72% | N/A | 61.12% | N/A | 0-shot evaluation | | ARC Challenge | 32.94% | 36.01% | 33.36% | 37.63% | 0-shot evaluation | | ARC Easy | 64.52% | 60.40% | 65.91% | 60.90% | 0-shot evaluation | | BoolQ | 50.24% | N/A | 52.29% | N/A | 0-shot evaluation | | PIQA | 75.46% | 74.37% | 75.63% | 75.19% | 0-shot evaluation | | HellaSwag | 48.56% | 64.71% | 48.46% | 64.50% | 0-shot evaluation | ## Using this Model ```python from transformers import AutoTokenizer import transformers import torch # Load Model and Pipeline model = "AdamLucek/Orpo-Llama-3.2-1B-40k" pipeline = transformers.pipeline( "text-generation", model=model, torch_dtype=torch.float16, device_map="auto", ) # Load Tokenizer tokenizer = AutoTokenizer.from_pretrained(model) # Generate Message messages = [{"role": "user", "content": "What is a language model?"}] prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) outputs = pipeline(prompt, max_new_tokens=1024, do_sample=True, temperature=0.3, top_k=50, top_p=0.95) print(outputs[0]["generated_text"]) ``` ## Training Statistics

## OpenLLM Leaderboard Metrics | Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |leaderboard | N/A| | | | | | | | | - leaderboard_bbh | N/A| | | | |0.3290| | | | - leaderboard_bbh_boolean_expressions | 1|none | 3|acc_norm |↑ |0.6840|± |0.0295| | - leaderboard_bbh_causal_judgement | 1|none | 3|acc_norm |↑ |0.5134|± |0.0366| | - leaderboard_bbh_date_understanding | 1|none | 3|acc_norm |↑ |0.1920|± |0.0250| | - leaderboard_bbh_disambiguation_qa | 1|none | 3|acc_norm |↑ |0.3880|± |0.0309| | - leaderboard_bbh_formal_fallacies | 1|none | 3|acc_norm |↑ |0.4680|± |0.0316| | - leaderboard_bbh_geometric_shapes | 1|none | 3|acc_norm |↑ |0.0000|± | 0| | - leaderboard_bbh_hyperbaton | 1|none | 3|acc_norm |↑ |0.4840|± |0.0317| | - leaderboard_bbh_logical_deduction_five_objects | 1|none | 3|acc_norm |↑ |0.2000|± |0.0253| | - leaderboard_bbh_logical_deduction_seven_objects | 1|none | 3|acc_norm |↑ |0.1360|± |0.0217| | - leaderboard_bbh_logical_deduction_three_objects | 1|none | 3|acc_norm |↑ |0.3440|± |0.0301| | - leaderboard_bbh_movie_recommendation | 1|none | 3|acc_norm |↑ |0.2280|± |0.0266| | - leaderboard_bbh_navigate | 1|none | 3|acc_norm |↑ |0.4200|± |0.0313| | - leaderboard_bbh_object_counting | 1|none | 3|acc_norm |↑ |0.3880|± |0.0309| | - leaderboard_bbh_penguins_in_a_table | 1|none | 3|acc_norm |↑ |0.1575|± |0.0303| | - leaderboard_bbh_reasoning_about_colored_objects | 1|none | 3|acc_norm |↑ |0.1280|± |0.0212| | - leaderboard_bbh_ruin_names | 1|none | 3|acc_norm |↑ |0.2000|± |0.0253| | - leaderboard_bbh_salient_translation_error_detection | 1|none | 3|acc_norm |↑ |0.2280|± |0.0266| | - leaderboard_bbh_snarks | 1|none | 3|acc_norm |↑ |0.5393|± |0.0375| | - leaderboard_bbh_sports_understanding | 1|none | 3|acc_norm |↑ |0.5240|± |0.0316| | - leaderboard_bbh_temporal_sequences | 1|none | 3|acc_norm |↑ |0.2000|± |0.0253| | - leaderboard_bbh_tracking_shuffled_objects_five_objects | 1|none | 3|acc_norm |↑ |0.1640|± |0.0235| | - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 1|none | 3|acc_norm |↑ |0.1400|± |0.0220| | - leaderboard_bbh_tracking_shuffled_objects_three_objects| 1|none | 3|acc_norm |↑ |0.3520|± |0.0303| | - leaderboard_bbh_web_of_lies | 1|none | 3|acc_norm |↑ |0.4880|± |0.0317| | - leaderboard_gpqa | N/A| | | | |0.2482| | | | - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.2576|± |0.0312| | - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.2436|± |0.0184| | - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.2433|± |0.0203| | - leaderboard_ifeval | 3|none | 0|inst_level_loose_acc |↑ |0.2962|± | N/A| | | |none | 0|inst_level_strict_acc |↑ |0.2842|± | N/A| | | |none | 0|prompt_level_loose_acc |↑ |0.1516|± |0.0154| | | |none | 0|prompt_level_strict_acc|↑ |0.1386|± |0.0149| | - leaderboard_math_hard | N/A| | | | | | | | | - leaderboard_math_algebra_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_math_counting_and_prob_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_math_geometry_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_math_intermediate_algebra_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_math_num_theory_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_math_prealgebra_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_math_precalculus_hard | 2|none | 4|exact_match |↑ |0.0000|± | 0| | - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.1222|± |0.0030| | - leaderboard_musr | N/A| | |avg acc_norm | |0.3433| | | | - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5120|± |0.0317| | - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.2500|± |0.0271| | - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.2680|± |0.0281|