---
license: llama2
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: TheBloke/CodeLlama-7B-Instruct-AWQ
model-index:
- name: CodeLlama-7B-Instruct-AWQ-FaVe-rank16-5epochs
  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. -->

# CodeLlama-7B-Instruct-AWQ-FaVe-rank16-5epochs

This model is a fine-tuned version of [TheBloke/CodeLlama-7B-Instruct-AWQ](https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-AWQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4559

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.2685 | 10   | 2.1904          |
| 2.1539        | 0.5369 | 20   | 1.3867          |
| 2.1539        | 0.8054 | 30   | 0.9114          |
| 0.9417        | 1.0738 | 40   | 0.7705          |
| 0.9417        | 1.3423 | 50   | 0.7068          |
| 0.632         | 1.6107 | 60   | 0.6554          |
| 0.632         | 1.8792 | 70   | 0.6145          |
| 0.5044        | 2.1477 | 80   | 0.5866          |
| 0.5044        | 2.4161 | 90   | 0.5553          |
| 0.4666        | 2.6846 | 100  | 0.5301          |
| 0.4666        | 2.9530 | 110  | 0.5144          |
| 0.366         | 3.2215 | 120  | 0.4953          |
| 0.366         | 3.4899 | 130  | 0.4918          |
| 0.342         | 3.7584 | 140  | 0.4698          |
| 0.342         | 4.0268 | 150  | 0.4638          |
| 0.2842        | 4.2953 | 160  | 0.4748          |
| 0.2842        | 4.5638 | 170  | 0.4599          |
| 0.2764        | 4.8322 | 180  | 0.4559          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1