--- language: - el - en license: apache-2.0 library_name: transformers pipeline_tag: text-generation base_model: glossAPI/apertus-8b-greek-cpt datasets: - glossAPI/apertus-8b-greek-cpt-modern-greek-train - glossAPI/greek-apertus-post-training-data tags: - apertus - greek - glossapi - instruct - public-three-benchmarks model-index: - name: Greek Apertus 8B — Greek maths tuning results: - task: type: text-generation dataset: name: GreekMMLU type: greekmmlu metrics: - type: accuracy name: accuracy (%) value: 70.44 - task: type: text-generation dataset: name: Greek IFEval type: ifeval-el metrics: - type: accuracy name: accuracy (%) value: 68.02 - task: type: text-generation dataset: name: Greek GSM8K type: gsm8k-el metrics: - type: accuracy name: accuracy (%) value: 61.49 --- # Greek Apertus 8B — Greek maths tuning 5,482 Greek maths rows and 4,496 replay rows. Three epochs, learning rate 5e-6, sequence length 4,096. ## Benchmarks Accuracy (%). | GreekMMLU | Greek IFEval | Greek GSM8K | |---:|---:|---:| | 70.44 | 68.02 | 61.49 | ## Repositories and checkpoints | Resource | Links | |---|---| | Instruction models | [Parent — Stage 1](https://huggingface.co/glossAPI/greek-apertus-8b-instruct/tree/stage1-sft-S1), [Next stage — Conversation](https://huggingface.co/glossAPI/greek-apertus-8b-instruct/tree/stage3-sft-chat-P), [Repository](https://huggingface.co/glossAPI/greek-apertus-8b-instruct) | | Post-training data | [Training data — Greek maths](https://huggingface.co/datasets/glossAPI/greek-apertus-post-training-data/tree/main/second_stage_sft/stage2-sft-recipe3), [Repository](https://huggingface.co/datasets/glossAPI/greek-apertus-post-training-data) | | Greek base | [base-avg30B-50B](https://huggingface.co/glossAPI/apertus-8b-greek-cpt/tree/base-avg30B-50B) | | Pre-training data | [Repository](https://huggingface.co/datasets/glossAPI/apertus-8b-greek-cpt-modern-greek-train) | | SFT data | [Repository](https://huggingface.co/datasets/glossAPI/greek-apertus-sft-data) | | Tokenizer | [Repository](https://huggingface.co/fffoivos/apertus-tokenizer-extension) | ## Licence Apache-2.0 for the model weights. ## Acknowledgements This work was implemented thanks to a grant by Swiss AI for compute on CSCS.