---
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: code-llama-sparql-lcquad-dbpedia
  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-sparql-lcquad-dbpedia

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: 0.1978

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1267        | 0.0710 | 20   | 1.1174          |
| 0.7096        | 0.1421 | 40   | 0.4625          |
| 0.3148        | 0.2131 | 60   | 0.3134          |
| 0.2716        | 0.2842 | 80   | 0.2705          |
| 0.2267        | 0.3552 | 100  | 0.2945          |
| 0.2494        | 0.4263 | 120  | 0.2441          |
| 0.2369        | 0.4973 | 140  | 0.2363          |
| 0.2397        | 0.5684 | 160  | 0.2311          |
| 0.2256        | 0.6394 | 180  | 0.2261          |
| 0.2091        | 0.7105 | 200  | 0.2336          |
| 0.218         | 0.7815 | 220  | 0.2161          |
| 0.222         | 0.8526 | 240  | 0.2116          |
| 0.2169        | 0.9236 | 260  | 0.2094          |
| 0.2058        | 0.9947 | 280  | 0.2058          |
| 0.2081        | 1.0657 | 300  | 0.2039          |
| 0.2049        | 1.1368 | 320  | 0.2029          |
| 0.1925        | 1.2078 | 340  | 0.2019          |
| 0.2123        | 1.2789 | 360  | 0.1989          |
| 0.1933        | 1.3499 | 380  | 0.1980          |
| 0.2009        | 1.4210 | 400  | 0.1978          |


### Framework versions

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