---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-7b-Instruct-hf
model-index:
- name: codellamafinetune4
  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. -->

# codellamafinetune4

This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9889

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.688         | 1.0   | 1    | 2.6763          |
| 2.1974        | 2.0   | 2    | 2.0364          |
| 1.6202        | 3.0   | 3    | 1.5093          |
| 1.0587        | 4.0   | 4    | 1.1951          |
| 0.6205        | 5.0   | 5    | 0.9933          |
| 0.3365        | 6.0   | 6    | 0.9511          |
| 0.2012        | 7.0   | 7    | 0.9777          |
| 0.1703        | 8.0   | 8    | 0.9889          |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
## Training procedure


### Framework versions


- PEFT 0.6.0