---
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-robots2
  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-robots2

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: 1.3843

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 20.4692       | 0.91  | 5    | 7.4399          |
| 12.9912       | 2.0   | 11   | 6.6074          |
| 10.1734       | 2.91  | 16   | 6.0225          |
| 9.8269        | 4.0   | 22   | 3.5503          |
| 5.2353        | 4.91  | 27   | 1.6505          |
| 1.6367        | 6.0   | 33   | 1.4912          |
| 1.4714        | 6.91  | 38   | 1.4201          |
| 1.3916        | 8.0   | 44   | 1.3933          |
| 1.2832        | 8.91  | 49   | 1.3882          |
| 1.2863        | 9.09  | 50   | 1.3843          |


### Framework versions

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