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---
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 |
|