---
license: llama2
base_model: codellama/CodeLlama-7b-Instruct-hf
tags:
- generated_from_trainer
model-index:
- name: code-llama-instruct-7b-text-to-sparql-axiom
  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. -->

# code-llama-instruct-7b-text-to-sparql-axiom

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: 0.1333

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3919        | 0.0710 | 20   | 1.3906          |
| 0.8712        | 0.1421 | 40   | 0.4591          |
| 0.2672        | 0.2131 | 60   | 0.2378          |
| 0.213         | 0.2842 | 80   | 0.2065          |
| 0.1697        | 0.3552 | 100  | 0.2208          |
| 0.2068        | 0.4263 | 120  | 0.1886          |
| 0.1808        | 0.4973 | 140  | 0.1843          |
| 0.2073        | 0.5684 | 160  | 0.1812          |
| 0.1833        | 0.6394 | 180  | 0.1735          |
| 0.1556        | 0.7105 | 200  | 0.1836          |
| 0.1813        | 0.7815 | 220  | 0.1688          |
| 0.166         | 0.8526 | 240  | 0.1642          |
| 0.1773        | 0.9236 | 260  | 0.1609          |
| 0.1514        | 0.9947 | 280  | 0.1597          |
| 0.1592        | 1.0657 | 300  | 0.1581          |
| 0.1632        | 1.1368 | 320  | 0.1552          |
| 0.1601        | 1.2078 | 340  | 0.1554          |
| 0.1529        | 1.2789 | 360  | 0.1523          |
| 0.1352        | 1.3499 | 380  | 0.1528          |
| 0.1601        | 1.4210 | 400  | 0.1496          |
| 0.1523        | 1.4920 | 420  | 0.1482          |
| 0.1568        | 1.5631 | 440  | 0.1482          |
| 0.1598        | 1.6341 | 460  | 0.1461          |
| 0.1432        | 1.7052 | 480  | 0.1471          |
| 0.158         | 1.7762 | 500  | 0.1430          |
| 0.1479        | 1.8472 | 520  | 0.1422          |
| 0.1488        | 1.9183 | 540  | 0.1429          |
| 0.1422        | 1.9893 | 560  | 0.1397          |
| 0.149         | 2.0604 | 580  | 0.1391          |
| 0.1352        | 2.1314 | 600  | 0.1381          |
| 0.1357        | 2.2025 | 620  | 0.1389          |
| 0.1519        | 2.2735 | 640  | 0.1369          |
| 0.1321        | 2.3446 | 660  | 0.1367          |
| 0.1381        | 2.4156 | 680  | 0.1361          |
| 0.1362        | 2.4867 | 700  | 0.1349          |
| 0.1329        | 2.5577 | 720  | 0.1351          |
| 0.1457        | 2.6288 | 740  | 0.1340          |
| 0.1267        | 2.6998 | 760  | 0.1336          |
| 0.1433        | 2.7709 | 780  | 0.1335          |
| 0.1343        | 2.8419 | 800  | 0.1333          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.10.1
- Tokenizers 0.19.1