metadata
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- conceptofmind/FLAN_2022
model-index:
- name: outputs
results: []
outputs
This model is a fine-tuned version of 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
Detailed results can be found here
| 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 |