---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0521HMA26H4
  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. -->

# G0521HMA26H4

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: 0.1030

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7533        | 0.09  | 10   | 1.3530          |
| 1.0176        | 0.18  | 20   | 0.4935          |
| 0.3275        | 0.27  | 30   | 0.1747          |
| 0.1534        | 0.36  | 40   | 0.1566          |
| 0.1477        | 0.45  | 50   | 0.1507          |
| 0.1476        | 0.54  | 60   | 0.1484          |
| 0.1456        | 0.63  | 70   | 0.1461          |
| 0.1465        | 0.73  | 80   | 0.1504          |
| 0.1386        | 0.82  | 90   | 0.1430          |
| 0.1341        | 0.91  | 100  | 0.1437          |
| 0.138         | 1.0   | 110  | 0.1362          |
| 0.1253        | 1.09  | 120  | 0.1360          |
| 0.1175        | 1.18  | 130  | 0.1205          |
| 0.1198        | 1.27  | 140  | 0.1219          |
| 0.1244        | 1.36  | 150  | 0.1200          |
| 0.1182        | 1.45  | 160  | 0.1153          |
| 0.1148        | 1.54  | 170  | 0.1119          |
| 0.1111        | 1.63  | 180  | 0.1223          |
| 0.11          | 1.72  | 190  | 0.1166          |
| 0.1126        | 1.81  | 200  | 0.1095          |
| 0.1113        | 1.9   | 210  | 0.1053          |
| 0.1052        | 1.99  | 220  | 0.1052          |
| 0.0971        | 2.08  | 230  | 0.1108          |
| 0.0968        | 2.18  | 240  | 0.1052          |
| 0.0927        | 2.27  | 250  | 0.1154          |
| 0.0946        | 2.36  | 260  | 0.1106          |
| 0.0946        | 2.45  | 270  | 0.1122          |
| 0.0868        | 2.54  | 280  | 0.1120          |
| 0.0825        | 2.63  | 290  | 0.1096          |
| 0.087         | 2.72  | 300  | 0.1056          |
| 0.0934        | 2.81  | 310  | 0.1038          |
| 0.0917        | 2.9   | 320  | 0.1030          |
| 0.0926        | 2.99  | 330  | 0.1030          |


### Framework versions

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