--- library_name: transformers tags: - unsloth license: mit datasets: - efederici/alpaca-vs-alpaca-orpo-dpo --- # Model Card for Model ID This is phi-3-mini-4k-instruct ORPO finetuning for the italian language over the Alpaca vs. Alpaca italian dataset: [efederici/alpaca-vs-alpaca-orpo-dpo](https://huggingface.co/datasets/efederici/alpaca-vs-alpaca-orpo-dpo) ## Model Details ### Model Description - **Developed by:** Diego Giorgini - **Funded by:** AI Technologies SRL - www.aitechnologies.it - **Language(s) (NLP):** Italian - **License:** llama3 - **Finetuned from model:** unsloth/Phi-3-mini-4k-instruct ## Training Details ### Environment unsloth: 2024.5 torch: 2.2 ### Training Data [efederici/alpaca-vs-alpaca-orpo-dpo](https://huggingface.co/datasets/efederici/alpaca-vs-alpaca-orpo-dpo): The Alpaca vs. Alpaca dataset is a curated blend of the Alpaca dataset and the Alpaca GPT-4 dataset, both available on HuggingFace Datasets. It uses the standard GPT dataset as the 'rejected' answer, steering the model towards the GPT-4 answer, which is considered as the 'chosen' one. ### Training Procedure #### Preprocessing [optional] - No preprocessing has been performed, except for formatting with the phi-3 chat_template from unsloth: ```tokenizer = get_chat_template(tokenizer, chat_template = "phi-3")``` #### Training Hyperparameters - **Training regime:** bf16 - **Model loading parameters:** ``` max_seq_length = 8192 dtype = None load_in_4bit = False ``` - **PEFT parameters:** ``` r = 64 lora_alpha = 64 lora_dropout = 0 bias = "none" random_state = 3407 use_rslora = False loftq_config = None ``` - **ORPOConfig parameters:** ``` max_length = 8192 max_prompt_length = max_seq_length//2 max_completion_length = max_seq_length//2 warmup_ratio = 0.1 weight_decay = 0.01 per_device_train_batch_size = 1 gradient_accumulation_steps = 16 learning_rate=8e-6 beta = 0.1 optim = "paged_adamw_8bit" lr_scheduler_type = "linear" num_train_epochs = 1 ``` #### Speeds, Sizes, Times 7h on an A100-40GB ## Model Card Contact diego.giorgini@icloud.com