---
license: llama2
base_model: lmsys/vicuna-7b-v1.5
tags:
- generated_from_trainer
datasets:
- truthful_qa
metrics:
- accuracy
model-index:
- name: vicuna_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. -->

# vicuna_mc_finetune

This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the truthful_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8867
- Accuracy: 0.2378

## 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: 0.0001
- 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: 5
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7307        | 1.0   | 109  | 1.5327          | 0.4024   |
| 1.4519        | 2.0   | 218  | 1.2341          | 0.7073   |
| 0.0207        | 3.0   | 327  | 2.2924          | 0.6280   |
| 1.5647        | 4.0   | 436  | 1.9344          | 0.2256   |
| 2.2047        | 5.0   | 545  | 1.9401          | 0.2256   |
| 2.016         | 6.0   | 654  | 1.8888          | 0.2256   |
| 1.625         | 7.0   | 763  | 1.9068          | 0.1768   |
| 2.0002        | 8.0   | 872  | 1.8909          | 0.1951   |
| 1.7906        | 9.0   | 981  | 1.8828          | 0.2195   |
| 1.5295        | 10.0  | 1090 | 1.8967          | 0.2195   |
| 1.7018        | 11.0  | 1199 | 1.8845          | 0.2378   |
| 1.8412        | 12.0  | 1308 | 1.8808          | 0.2073   |
| 2.4396        | 13.0  | 1417 | 1.8816          | 0.2012   |
| 1.8643        | 14.0  | 1526 | 1.8827          | 0.2012   |
| 1.7271        | 15.0  | 1635 | 1.8844          | 0.2256   |
| 1.851         | 16.0  | 1744 | 1.8720          | 0.2134   |
| 1.7633        | 17.0  | 1853 | 1.8786          | 0.2134   |
| 2.6586        | 18.0  | 1962 | 1.8723          | 0.25     |
| 2.0078        | 19.0  | 2071 | 1.8770          | 0.2439   |
| 1.4072        | 20.0  | 2180 | 1.8867          | 0.2378   |


### Framework versions

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