---
license: other
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b-it
model-index:
- name: ft-google-gemma-2b-it-qlora
  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. -->

# ft-google-gemma-2b-it-qlora

This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7958

## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0077        | 100.0  | 100  | 2.3782          |
| 0.0005        | 200.0  | 200  | 2.9807          |
| 0.0004        | 300.0  | 300  | 3.1002          |
| 0.0004        | 400.0  | 400  | 3.1932          |
| 0.0004        | 500.0  | 500  | 3.2895          |
| 0.0004        | 600.0  | 600  | 3.3658          |
| 0.0003        | 700.0  | 700  | 3.3978          |
| 0.0004        | 800.0  | 800  | 3.4260          |
| 0.0004        | 900.0  | 900  | 3.5341          |
| 0.0003        | 1000.0 | 1000 | 3.5190          |
| 0.0004        | 1100.0 | 1100 | 3.5536          |
| 0.0003        | 1200.0 | 1200 | 3.5967          |
| 0.0003        | 1300.0 | 1300 | 3.6020          |
| 0.0004        | 1400.0 | 1400 | 3.6300          |
| 0.0004        | 1500.0 | 1500 | 3.6133          |
| 0.0003        | 1600.0 | 1600 | 3.7128          |
| 0.0003        | 1700.0 | 1700 | 3.7430          |
| 0.0003        | 1800.0 | 1800 | 3.7682          |
| 0.0003        | 1900.0 | 1900 | 3.7548          |
| 0.0003        | 2000.0 | 2000 | 3.7958          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2