---
base_model: codellama/CodeLlama-7b-hf
library_name: peft
license: llama2
tags:
- generated_from_trainer
model-index:
- name: sparql-code-llama
  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. -->

# sparql-code-llama

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: 0.4088

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.695         | 0.0838 | 50   | 0.7324          |
| 0.4445        | 0.1676 | 100  | 0.5458          |
| 0.4184        | 0.2515 | 150  | 0.4852          |
| 0.4081        | 0.3353 | 200  | 0.4599          |
| 0.3996        | 0.4191 | 250  | 0.4389          |
| 0.3944        | 0.5029 | 300  | 0.4256          |
| 0.3925        | 0.5868 | 350  | 0.4150          |
| 0.3957        | 0.6706 | 400  | 0.4088          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0