---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0515HMA24H
  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. -->

# G0515HMA24H

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: 0.1169

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.171         | 0.09  | 10   | 2.7380          |
| 2.343         | 0.18  | 20   | 1.7302          |
| 1.2081        | 0.27  | 30   | 0.5724          |
| 0.3215        | 0.36  | 40   | 0.1716          |
| 0.1576        | 0.45  | 50   | 0.1560          |
| 0.1519        | 0.54  | 60   | 0.1512          |
| 0.1491        | 0.63  | 70   | 0.1486          |
| 0.1507        | 0.73  | 80   | 0.1504          |
| 0.1428        | 0.82  | 90   | 0.1496          |
| 0.1455        | 0.91  | 100  | 0.1486          |
| 0.1485        | 1.0   | 110  | 0.1495          |
| 0.1441        | 1.09  | 120  | 0.1485          |
| 0.1456        | 1.18  | 130  | 0.1489          |
| 0.1458        | 1.27  | 140  | 0.1466          |
| 0.1484        | 1.36  | 150  | 0.1462          |
| 0.1424        | 1.45  | 160  | 0.1481          |
| 0.1426        | 1.54  | 170  | 0.1445          |
| 0.1447        | 1.63  | 180  | 0.1424          |
| 0.1448        | 1.72  | 190  | 0.1439          |
| 0.1398        | 1.81  | 200  | 0.1396          |
| 0.1386        | 1.9   | 210  | 0.1333          |
| 0.133         | 1.99  | 220  | 0.1277          |
| 0.1266        | 2.08  | 230  | 0.1289          |
| 0.126         | 2.18  | 240  | 0.1236          |
| 0.1222        | 2.27  | 250  | 0.1262          |
| 0.1248        | 2.36  | 260  | 0.1237          |
| 0.1217        | 2.45  | 270  | 0.1209          |
| 0.1197        | 2.54  | 280  | 0.1205          |
| 0.1155        | 2.63  | 290  | 0.1188          |
| 0.1123        | 2.72  | 300  | 0.1175          |
| 0.1195        | 2.81  | 310  | 0.1171          |
| 0.1192        | 2.9   | 320  | 0.1169          |
| 0.1166        | 2.99  | 330  | 0.1169          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0