---
base_model: bofenghuang/vigogne-2-13b-instruct
tags:
- generated_from_trainer
model-index:
- name: PointCon-Vigogne-13B-LoRA
  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. -->

# PointCon-Vigogne-13B-LoRA

This model is a fine-tuned version of [bofenghuang/vigogne-2-13b-instruct](https://huggingface.co/bofenghuang/vigogne-2-13b-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8656

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0885        | 0.1   | 30   | 2.0357          |
| 2.0024        | 0.19  | 60   | 1.9733          |
| 1.9995        | 0.29  | 90   | 1.9406          |
| 1.9752        | 0.38  | 120  | 1.9285          |
| 1.9235        | 0.48  | 150  | 1.9060          |
| 1.9345        | 0.57  | 180  | 1.8924          |
| 1.8576        | 0.67  | 210  | 1.8818          |
| 1.8693        | 0.76  | 240  | 1.8734          |
| 1.8686        | 0.86  | 270  | 1.8695          |
| 1.8814        | 0.95  | 300  | 1.8656          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1