---
library_name: transformers
tags:
- unsloth
- trl
- sft
license: mit
datasets:
- elyza/JaMARD
- EleutherAI/hendrycks_math
language:
- ja
- en
base_model:
- sbintuitions/sarashina2-13b
pipeline_tag: text-generation
---
# Model Card for Sarashina2-13b-finetuned-v1 🧮📘

A Japanese-English bilingual language model fine-tuned on 100 randomly shuffled samples from math datasets. Based on `sbintuitions/sarashina2-13b` and trained using `unsloth`, `trl`, and `sft`.

## Model Details

### Description

🧠 Fine-tuned transformer model for solving math problems and answering technical questions in 🇯🇵 Japanese and 🇺🇸 English.

- **Base Model:** sbintuitions/sarashina2-13b
- **License:** MIT
- **Languages:** Japanese, English
- **Model Type:** Transformer (Causal LM)


## Limitations

⚠️ Known limitations:
- May generate incorrect or biased answers
- May hallucinate explanations

🔍 Always verify important outputs.

## Get Started

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Mori-kamiyama/sarashina-13B-finetuned-v1")
tokenizer = AutoTokenizer.from_pretrained("Mori-kamiyama/sarashina-13B-finetuned-v1")
```

## Training Data

🧮 Fine-tuned using 100 randomly shuffled samples from:
- `elyza/JaMARD` (Japanese instruction tuning)
- `EleutherAI/hendrycks_math` (math reasoning)

## Architecture

- Transformer (Causal LM)
- Fine-tuned with TRL + Unsloth