---
base_model: codellama/CodeLlama-7b-Instruct-hf
library_name: peft
license: llama2
tags:
- generated_from_trainer
model-index:
- name: codellama-adb-sdk
  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-adb-sdk

This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9731

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2695        | 0.05  | 100  | 0.5778          |
| 0.0568        | 0.1   | 200  | 0.7456          |
| 0.0411        | 0.15  | 300  | 0.8092          |
| 0.0366        | 0.2   | 400  | 0.8567          |
| 0.032         | 0.25  | 500  | 0.8574          |
| 0.0256        | 0.3   | 600  | 0.8451          |
| 0.0258        | 0.35  | 700  | 0.8729          |
| 0.0245        | 0.4   | 800  | 0.8760          |
| 0.0222        | 0.45  | 900  | 0.8999          |
| 0.0199        | 0.5   | 1000 | 0.8617          |
| 0.0215        | 0.55  | 1100 | 0.9148          |
| 0.0226        | 0.6   | 1200 | 0.9237          |
| 0.0206        | 0.65  | 1300 | 0.9307          |
| 0.0209        | 0.7   | 1400 | 0.9392          |
| 0.0184        | 0.75  | 1500 | 0.9659          |
| 0.0189        | 0.8   | 1600 | 0.9492          |
| 0.0202        | 0.85  | 1700 | 0.9660          |
| 0.0192        | 0.9   | 1800 | 0.9668          |
| 0.0176        | 0.95  | 1900 | 0.9722          |
| 0.0186        | 1.0   | 2000 | 0.9731          |


### Framework versions

- PEFT 0.13.2.dev0
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1