---
license: other
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: microsoft/Orca-2-7b
model-index:
- name: 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. -->

# lora

This model is a fine-tuned version of [microsoft/Orca-2-7b](https://huggingface.co/microsoft/Orca-2-7b) on the Pretrain_Basic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4452

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5009        | 0.1586 | 500  | 0.4964          |
| 0.4641        | 0.3172 | 1000 | 0.4591          |
| 0.4514        | 0.4758 | 1500 | 0.4516          |
| 0.4522        | 0.6344 | 2000 | 0.4482          |
| 0.4436        | 0.7930 | 2500 | 0.4459          |
| 0.4463        | 0.9516 | 3000 | 0.4452          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.0.1+cu118
- Datasets 2.17.1
- Tokenizers 0.19.1