---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b
datasets:
- chansung/no_robots_only_coding
model-index:
- name: gemma-7b-sft-qlora-no-robots15
  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. -->

# gemma-7b-sft-qlora-no-robots15

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the chansung/no_robots_only_coding dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2808

## 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
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 21.9058       | 0.91  | 5    | 7.6562          |
| 13.5645       | 2.0   | 11   | 6.6359          |
| 10.2613       | 2.91  | 16   | 6.0754          |
| 9.903         | 4.0   | 22   | 3.1116          |
| 4.594         | 4.91  | 27   | 1.6371          |
| 1.6122        | 6.0   | 33   | 1.4160          |
| 1.3971        | 6.91  | 38   | 1.3411          |
| 1.2757        | 8.0   | 44   | 1.3074          |
| 1.1233        | 8.91  | 49   | 1.2756          |
| 0.9741        | 10.0  | 55   | 1.2736          |
| 0.9266        | 10.91 | 60   | 1.2791          |
| 0.8584        | 12.0  | 66   | 1.2753          |
| 0.8714        | 12.91 | 71   | 1.2842          |
| 0.8421        | 13.64 | 75   | 1.2808          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2