---
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: fine_tuning_codellama
  results: []
library_name: peft
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/chebbichafik133/sql-convert/runs/3q5mg1tl)
# fine_tuning_codellama

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: 0.1513

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: True
- _load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
- bnb_4bit_quant_storage: uint8
- load_in_4bit: False
- load_in_8bit: True
### 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: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1085        | 0.1010 | 20   | 1.0942          |
| 0.729         | 0.2020 | 40   | 0.5856          |
| 0.4941        | 0.3030 | 60   | 0.3775          |
| 0.2508        | 0.4040 | 80   | 0.2868          |
| 0.2139        | 0.5051 | 100  | 0.2528          |
| 0.2612        | 0.6061 | 120  | 0.2115          |
| 0.154         | 0.7071 | 140  | 0.2073          |
| 0.2558        | 0.8081 | 160  | 0.1936          |
| 0.1553        | 0.9091 | 180  | 0.1832          |
| 0.1831        | 1.0101 | 200  | 0.1872          |
| 0.2135        | 1.1111 | 220  | 0.1729          |
| 0.1278        | 1.2121 | 240  | 0.1724          |
| 0.21          | 1.3131 | 260  | 0.1676          |
| 0.1328        | 1.4141 | 280  | 0.1619          |
| 0.1731        | 1.5152 | 300  | 0.1651          |
| 0.1668        | 1.6162 | 320  | 0.1577          |
| 0.1259        | 1.7172 | 340  | 0.1565          |
| 0.191         | 1.8182 | 360  | 0.1543          |
| 0.129         | 1.9192 | 380  | 0.1515          |
| 0.1693        | 2.0202 | 400  | 0.1513          |


### Framework versions

- PEFT 0.6.0.dev0
- Transformers 4.42.0.dev0
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1