---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: Gemma2B-StaproCoder
  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. -->

# Gemma2B-StaproCoder

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: 0.2988

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.733         | 0.05  | 100  | 0.5294          |
| 0.5149        | 0.1   | 200  | 0.4275          |
| 0.2925        | 0.15  | 300  | 0.3854          |
| 0.3588        | 0.2   | 400  | 0.3794          |
| 0.3145        | 0.25  | 500  | 0.3766          |
| 0.4036        | 0.3   | 600  | 0.3728          |
| 0.4822        | 0.35  | 700  | 0.3553          |
| 0.3456        | 0.4   | 800  | 0.3428          |
| 0.3978        | 0.45  | 900  | 0.3367          |
| 0.2692        | 0.5   | 1000 | 0.3365          |
| 0.4038        | 0.55  | 1100 | 0.3203          |
| 0.3345        | 0.6   | 1200 | 0.3210          |
| 0.2668        | 0.65  | 1300 | 0.3130          |
| 0.2617        | 0.7   | 1400 | 0.3103          |
| 0.2657        | 0.75  | 1500 | 0.3099          |
| 0.2633        | 0.8   | 1600 | 0.3041          |
| 0.4033        | 0.85  | 1700 | 0.3045          |
| 0.2208        | 0.9   | 1800 | 0.3017          |
| 0.2646        | 0.95  | 1900 | 0.2989          |
| 0.3054        | 1.0   | 2000 | 0.2988          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2