---
license: mit
datasets:
- openai/MMMLU
- argilla/FinePersonas-v0.1
- SkunkworksAI/reasoning-0.01
- fka/awesome-chatgpt-prompts
metrics:
- accuracy
- bleu
- bertscore
- bleurt
base_model:
- meta-llama/Llama-3.2-11B-Vision-Instruct
- nvidia/NVLM-D-72B
- openai/whisper-large-v3-turbo
new_version: meta-llama/Llama-3.1-8B-Instruct
pipeline_tag: question-answering
library_name: adapter-transformers

from transformers import AutoModelForQuestionAnswering, Trainer, TrainingArguments
model = AutoModelForQuestionAnswering.from_pretrained("your-model-name")

pip install transformers datasets

training_args = TrainingArguments(
    output_dir='./results', 
    num_train_epochs=3, 
    per_device_train_batch_size=16,
    evaluation_strategy="epoch"
)

---eval_results = trainer.evaluate()
print(eval_results)