---
license: llama2
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: codellama-7b-text-to-sql
  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-text-to-sql

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: 0.4224
- Rouge Scores: {'rouge1': 0.9523274691414706, 'rouge2': 0.8974742261714255, 'rougeL': 0.9171288478946306, 'rougeLsum': 0.9523427810006704}
- Bleu Scores: [0.9655707421980068, 0.9566701190306537, 0.9459215028465041, 0.9346533822146271]
- Gen Len: 138.6233

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge Scores                                                                                                                | Bleu Scores                                                                      | Gen Len  |
|:-------------:|:-----:|:-----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
| 0.4229        | 1.0   | 4800  | 0.4162          | {'rouge1': 0.9506510098188024, 'rouge2': 0.8949972495187106, 'rougeL': 0.9142255494550289, 'rougeLsum': 0.9506551339456668} | [0.9637759028147137, 0.9546609970402782, 0.9437656479747901, 0.9323669423057117] | 138.6233 |
| 0.3314        | 2.0   | 9600  | 0.4004          | {'rouge1': 0.9524326989909003, 'rouge2': 0.8987509624898048, 'rougeL': 0.9179414410323365, 'rougeLsum': 0.9524550499725172} | [0.9652102001679345, 0.9563139443363083, 0.9456856232691524, 0.9345677892198804] | 138.6233 |
| 0.2666        | 3.0   | 14400 | 0.4224          | {'rouge1': 0.9523274691414706, 'rouge2': 0.8974742261714255, 'rougeL': 0.9171288478946306, 'rougeLsum': 0.9523427810006704} | [0.9655707421980068, 0.9566701190306537, 0.9459215028465041, 0.9346533822146271] | 138.6233 |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2