---
license: gemma
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: Gemma2b-APPS
  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-APPS

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: 1.2944

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2046        | 0.04  | 100  | 1.2184          |
| 1.0393        | 0.08  | 200  | 1.1178          |
| 1.064         | 0.12  | 300  | 1.1963          |
| 1.0558        | 0.16  | 400  | 1.2121          |
| 0.9774        | 0.2   | 500  | 1.1823          |
| 1.0325        | 0.24  | 600  | 1.1829          |
| 1.0572        | 0.28  | 700  | 1.1875          |
| 0.9972        | 0.32  | 800  | 1.1901          |
| 0.9901        | 0.36  | 900  | 1.2049          |
| 1.0587        | 0.4   | 1000 | 1.2187          |
| 1.0643        | 0.44  | 1100 | 1.2270          |
| 1.1095        | 0.48  | 1200 | 1.2266          |
| 1.0179        | 0.52  | 1300 | 1.2468          |
| 1.0581        | 0.56  | 1400 | 1.2480          |
| 1.0722        | 0.6   | 1500 | 1.2642          |
| 1.1467        | 0.64  | 1600 | 1.2622          |
| 1.0536        | 0.68  | 1700 | 1.2816          |
| 1.0757        | 0.72  | 1800 | 1.2840          |
| 1.1504        | 0.76  | 1900 | 1.2884          |
| 1.1494        | 0.8   | 2000 | 1.2870          |
| 1.1206        | 0.84  | 2100 | 1.2888          |
| 1.0454        | 0.88  | 2200 | 1.2938          |
| 1.1487        | 0.92  | 2300 | 1.2944          |
| 1.1521        | 0.96  | 2400 | 1.2945          |
| 1.1155        | 1.0   | 2500 | 1.2944          |


### Framework versions

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