---
license: llama2
base_model: codellama/CodeLlama-7b-Instruct-hf
tags:
- generated_from_trainer
model-index:
- name: codellama-7b-sft-lora-func-names
  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. -->

# codellama-7b-sft-lora-func-names

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: 0.7084

## 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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 900

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7541        | 0.01  | 180  | 0.7222          |
| 0.7126        | 0.01  | 360  | 0.7118          |
| 0.7342        | 0.02  | 540  | 0.7100          |
| 0.7216        | 0.03  | 720  | 0.7083          |
| 0.7171        | 0.04  | 900  | 0.7084          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1