---
license: llama2
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: codellama2-finetuned-codex
  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. -->

# codellama2-finetuned-codex

This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2549

## 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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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_ratio: 0.03
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.876         | 0.43  | 20   | 1.7743          |
| 1.6213        | 0.85  | 40   | 1.4426          |
| 1.0392        | 1.28  | 60   | 0.9086          |
| 0.6962        | 1.7   | 80   | 0.6664          |
| 0.529         | 2.13  | 100  | 0.5439          |
| 0.4614        | 2.55  | 120  | 0.4650          |
| 0.4264        | 2.98  | 140  | 0.4218          |
| 0.376         | 3.4   | 160  | 0.3951          |
| 0.3665        | 3.83  | 180  | 0.3722          |
| 0.3398        | 4.26  | 200  | 0.3559          |
| 0.3198        | 4.68  | 220  | 0.3389          |
| 0.3263        | 5.11  | 240  | 0.3317          |
| 0.2952        | 5.53  | 260  | 0.3223          |
| 0.2871        | 5.96  | 280  | 0.3136          |
| 0.2861        | 6.38  | 300  | 0.3084          |
| 0.2899        | 6.81  | 320  | 0.3021          |
| 0.2769        | 7.23  | 340  | 0.2982          |
| 0.2541        | 7.66  | 360  | 0.2951          |
| 0.2421        | 8.09  | 380  | 0.2914          |
| 0.2275        | 8.51  | 400  | 0.2887          |
| 0.26          | 8.94  | 420  | 0.2799          |
| 0.2275        | 9.36  | 440  | 0.2797          |
| 0.2291        | 9.79  | 460  | 0.2722          |
| 0.2222        | 10.21 | 480  | 0.2744          |
| 0.2391        | 10.64 | 500  | 0.2721          |
| 0.208         | 11.06 | 520  | 0.2671          |
| 0.2012        | 11.49 | 540  | 0.2691          |
| 0.2092        | 11.91 | 560  | 0.2619          |
| 0.1761        | 12.34 | 580  | 0.2636          |
| 0.2248        | 12.77 | 600  | 0.2596          |
| 0.1803        | 13.19 | 620  | 0.2611          |
| 0.2022        | 13.62 | 640  | 0.2597          |
| 0.2006        | 14.04 | 660  | 0.2578          |
| 0.1864        | 14.47 | 680  | 0.2561          |
| 0.1933        | 14.89 | 700  | 0.2560          |
| 0.1892        | 15.32 | 720  | 0.2570          |
| 0.192         | 15.74 | 740  | 0.2562          |
| 0.1883        | 16.17 | 760  | 0.2553          |
| 0.1781        | 16.6  | 780  | 0.2549          |
| 0.1705        | 17.02 | 800  | 0.2560          |
| 0.181         | 17.45 | 820  | 0.2566          |
| 0.1552        | 17.87 | 840  | 0.2551          |
| 0.173         | 18.3  | 860  | 0.2560          |
| 0.1934        | 18.72 | 880  | 0.2557          |
| 0.1754        | 19.15 | 900  | 0.2555          |
| 0.1796        | 19.57 | 920  | 0.2555          |
| 0.1745        | 20.0  | 940  | 0.2555          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2