---
license: llama2
base_model: codellama/CodeLlama-13b-hf
tags:
- generated_from_trainer
model-index:
- name: code-llama-13b-text-to-sparql
  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-13b-text-to-sparql

This model is a fine-tuned version of [codellama/CodeLlama-13b-hf](https://huggingface.co/codellama/CodeLlama-13b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1870

## 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: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1121        | 0.0710 | 20   | 1.0865          |
| 0.6067        | 0.1421 | 40   | 0.3437          |
| 0.2982        | 0.2131 | 60   | 0.2775          |
| 0.2433        | 0.2842 | 80   | 0.2465          |
| 0.2162        | 0.3552 | 100  | 0.2657          |
| 0.2308        | 0.4263 | 120  | 0.2303          |
| 0.2356        | 0.4973 | 140  | 0.2217          |
| 0.239         | 0.5684 | 160  | 0.2167          |
| 0.2159        | 0.6394 | 180  | 0.2112          |
| 0.2005        | 0.7105 | 200  | 0.2217          |
| 0.2177        | 0.7815 | 220  | 0.2070          |
| 0.2048        | 0.8526 | 240  | 0.2018          |
| 0.2092        | 0.9236 | 260  | 0.1976          |
| 0.2057        | 0.9947 | 280  | 0.1959          |
| 0.198         | 1.0657 | 300  | 0.1929          |
| 0.1988        | 1.1368 | 320  | 0.1908          |
| 0.1886        | 1.2078 | 340  | 0.1906          |
| 0.1927        | 1.2789 | 360  | 0.1883          |
| 0.1841        | 1.3499 | 380  | 0.1872          |
| 0.1863        | 1.4210 | 400  | 0.1870          |


### Framework versions

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