---
license: mit
base_model: gpt2-large
tags:
- generated_from_trainer
datasets:
- customized
model-index:
- name: gpt2-large-lora-sft
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gpt2-large-lora-sft

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the customized dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.00013
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- total_train_batch_size: 6
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.5

### Training results



### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Mikivis__gpt2-large-lora-sft)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 28.05   |
| ARC (25-shot)         | 26.79          |
| HellaSwag (10-shot)   | 44.15    |
| MMLU (5-shot)         | 25.82         |
| TruthfulQA (0-shot)   | 39.06   |
| Winogrande (5-shot)   | 55.09   |
| GSM8K (5-shot)        | 0.0        |
| DROP (3-shot)         | 5.46         |