---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: Deci/DeciLM-7B
datasets:
- generator
model-index:
- name: deci7bit-lora-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. -->

# deci7bit-lora-sql

This model is a fine-tuned version of [Deci/DeciLM-7B](https://huggingface.co./Deci/DeciLM-7B) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3593

## 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: 1399
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7841        | 0.06  | 20   | 0.5204          |
| 0.4837        | 0.11  | 40   | 0.4376          |
| 0.4325        | 0.17  | 60   | 0.4122          |
| 0.4112        | 0.23  | 80   | 0.4029          |
| 0.4028        | 0.28  | 100  | 0.3925          |
| 0.3958        | 0.34  | 120  | 0.3855          |
| 0.3895        | 0.4   | 140  | 0.3816          |
| 0.3818        | 0.45  | 160  | 0.3784          |
| 0.3753        | 0.51  | 180  | 0.3756          |
| 0.3722        | 0.56  | 200  | 0.3734          |
| 0.3687        | 0.62  | 220  | 0.3702          |
| 0.3678        | 0.68  | 240  | 0.3665          |
| 0.3636        | 0.73  | 260  | 0.3627          |
| 0.3582        | 0.79  | 280  | 0.3580          |
| 0.3594        | 0.85  | 300  | 0.3593          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2