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---
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
|