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---
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 |