---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- truthful_qa
metrics:
- accuracy
model-index:
- name: llama_mc_finetune
  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. -->

# llama_mc_finetune

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 truthful_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3667
- Accuracy: 0.8476

## 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: 0.0002
- train_batch_size: 6
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6688        | 1.0   | 109  | 2.2295          | 0.2988   |
| 1.044         | 2.0   | 218  | 2.1568          | 0.3354   |
| 0.3249        | 3.0   | 327  | 0.7980          | 0.7195   |
| 1.3202        | 4.0   | 436  | 2.2679          | 0.1768   |
| 1.325         | 5.0   | 545  | 0.9487          | 0.8232   |
| 0.0001        | 6.0   | 654  | 1.3517          | 0.8171   |
| 1.8235        | 7.0   | 763  | 1.5762          | 0.7622   |
| 0.0001        | 8.0   | 872  | 1.5415          | 0.8415   |
| 0.0           | 9.0   | 981  | 1.1195          | 0.8110   |
| 0.0           | 10.0  | 1090 | 1.2257          | 0.8232   |
| 0.0           | 11.0  | 1199 | 1.3680          | 0.8171   |
| 0.0           | 12.0  | 1308 | 1.3485          | 0.8171   |
| 0.0           | 13.0  | 1417 | 1.3482          | 0.8171   |
| 0.0           | 14.0  | 1526 | 1.3481          | 0.8171   |
| 0.0           | 15.0  | 1635 | 1.3628          | 0.8415   |
| 0.0           | 16.0  | 1744 | 1.3643          | 0.8476   |
| 0.0           | 17.0  | 1853 | 1.3649          | 0.8476   |
| 0.0           | 18.0  | 1962 | 1.3659          | 0.8476   |
| 0.0           | 19.0  | 2071 | 1.3663          | 0.8476   |
| 0.0           | 20.0  | 2180 | 1.3667          | 0.8476   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1