---
base_model: google/gemma-2b
library_name: peft
license: gemma
metrics:
- accuracy
tags:
- trl
- reward-trainer
- generated_from_trainer
model-index:
- name: 0809_031041-google-gemma-2b
  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. -->

# 0809_031041-google-gemma-2b

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3773
- Accuracy: 0.8239

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4824        | 0.3546 | 50   | 0.5036          | 0.7367   |
| 0.3486        | 0.7092 | 100  | 0.4458          | 0.7746   |
| 0.3555        | 1.0638 | 150  | 0.4337          | 0.8030   |
| 0.3447        | 1.4184 | 200  | 0.4066          | 0.8239   |
| 0.3008        | 1.7730 | 250  | 0.3979          | 0.8258   |
| 0.3857        | 2.1277 | 300  | 0.3888          | 0.8390   |
| 0.2754        | 2.4823 | 350  | 0.3760          | 0.8314   |
| 0.4746        | 2.8369 | 400  | 0.3798          | 0.8258   |
| 0.3281        | 3.1915 | 450  | 0.3734          | 0.8258   |
| 0.3149        | 3.5461 | 500  | 0.3827          | 0.8277   |
| 0.2695        | 3.9007 | 550  | 0.3720          | 0.8277   |
| 0.2524        | 4.2553 | 600  | 0.3758          | 0.8239   |
| 0.2197        | 4.6099 | 650  | 0.3768          | 0.8220   |
| 0.251         | 4.9645 | 700  | 0.3773          | 0.8239   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1