---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: GOLM3
  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. -->

# GOLM3

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: 0.1033

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 80
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8196        | 0.09  | 10   | 1.4618          |
| 1.0741        | 0.18  | 20   | 0.5866          |
| 0.3626        | 0.27  | 30   | 0.1793          |
| 0.1587        | 0.36  | 40   | 0.1503          |
| 0.1454        | 0.45  | 50   | 0.1476          |
| 0.1461        | 0.54  | 60   | 0.1476          |
| 0.143         | 0.63  | 70   | 0.1443          |
| 0.1452        | 0.73  | 80   | 0.1424          |
| 0.1345        | 0.82  | 90   | 0.1372          |
| 0.1286        | 0.91  | 100  | 0.1308          |
| 0.131         | 1.0   | 110  | 0.1317          |
| 0.123         | 1.09  | 120  | 0.1265          |
| 0.1161        | 1.18  | 130  | 0.1272          |
| 0.1188        | 1.27  | 140  | 0.1170          |
| 0.1197        | 1.36  | 150  | 0.1149          |
| 0.1139        | 1.45  | 160  | 0.1146          |
| 0.1122        | 1.54  | 170  | 0.1117          |
| 0.1093        | 1.63  | 180  | 0.1098          |
| 0.1093        | 1.72  | 190  | 0.1085          |
| 0.1096        | 1.81  | 200  | 0.1068          |
| 0.1086        | 1.9   | 210  | 0.1064          |
| 0.107         | 1.99  | 220  | 0.1065          |
| 0.0961        | 2.08  | 230  | 0.1069          |
| 0.0946        | 2.18  | 240  | 0.1061          |
| 0.0883        | 2.27  | 250  | 0.1048          |
| 0.0933        | 2.36  | 260  | 0.1039          |
| 0.0904        | 2.45  | 270  | 0.1058          |
| 0.0862        | 2.54  | 280  | 0.1057          |
| 0.0818        | 2.63  | 290  | 0.1047          |
| 0.0852        | 2.72  | 300  | 0.1046          |
| 0.0895        | 2.81  | 310  | 0.1048          |
| 0.0914        | 2.9   | 320  | 0.1044          |
| 0.0909        | 2.99  | 330  | 0.1033          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1