---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- conceptofmind/FLAN_2022
model-index:
- name: outputs
  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. -->

# outputs

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the conceptofmind/FLAN_2022 dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1.0

### Training results



### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- 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_synapsoft__Llama-2-7b-hf-flan2022-1.2M)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 41.68   |
| ARC (25-shot)         | 23.29          |
| HellaSwag (10-shot)   | 78.46    |
| MMLU (5-shot)         | 42.33         |
| TruthfulQA (0-shot)   | 37.97   |
| Winogrande (5-shot)   | 75.53   |
| GSM8K (5-shot)        | 4.47        |
| DROP (3-shot)         | 29.66         |