---
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
- ipex
- GPU Max 1100
- Intel(R) Data Center GPU Max 1100
datasets:
- generator
base_model: google/gemma-2b
model-index:
- name: gemma-finetuning
  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-finetuning

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1674

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training Hardware

Intel(R) Data Center GPU Max 1100

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 593

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8606        | 0.82  | 100  | 2.5425          |
| 2.4479        | 1.64  | 200  | 2.3304          |
| 2.3077        | 2.46  | 300  | 2.2351          |
| 2.2398        | 3.28  | 400  | 2.1914          |
| 2.2083        | 4.1   | 500  | 2.1674          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.0.1a0+cxx11.abi
- Datasets 2.18.0
- Tokenizers 0.15.2