---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0519ABLATION1V1
  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. -->

# G0519ABLATION1V1

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: 0.1220

## 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2296        | 0.09  | 10   | 2.9618          |
| 2.6424        | 0.18  | 20   | 2.1739          |
| 1.7328        | 0.27  | 30   | 1.1890          |
| 0.7887        | 0.36  | 40   | 0.3608          |
| 0.233         | 0.45  | 50   | 0.1685          |
| 0.1612        | 0.54  | 60   | 0.1533          |
| 0.1514        | 0.63  | 70   | 0.1494          |
| 0.1517        | 0.73  | 80   | 0.1488          |
| 0.142         | 0.82  | 90   | 0.1491          |
| 0.1459        | 0.91  | 100  | 0.1478          |
| 0.1487        | 1.0   | 110  | 0.1481          |
| 0.1431        | 1.09  | 120  | 0.1477          |
| 0.1443        | 1.18  | 130  | 0.1467          |
| 0.1448        | 1.27  | 140  | 0.1453          |
| 0.1465        | 1.36  | 150  | 0.1442          |
| 0.1404        | 1.45  | 160  | 0.1448          |
| 0.1428        | 1.54  | 170  | 0.1444          |
| 0.1424        | 1.63  | 180  | 0.1405          |
| 0.1421        | 1.72  | 190  | 0.1413          |
| 0.1371        | 1.81  | 200  | 0.1390          |
| 0.1376        | 1.9   | 210  | 0.1339          |
| 0.1351        | 1.99  | 220  | 0.1293          |
| 0.1296        | 2.08  | 230  | 0.1285          |
| 0.1277        | 2.18  | 240  | 0.1271          |
| 0.1269        | 2.27  | 250  | 0.1276          |
| 0.1286        | 2.36  | 260  | 0.1252          |
| 0.1283        | 2.45  | 270  | 0.1267          |
| 0.1244        | 2.54  | 280  | 0.1252          |
| 0.1213        | 2.63  | 290  | 0.1230          |
| 0.12          | 2.72  | 300  | 0.1220          |
| 0.1263        | 2.81  | 310  | 0.1219          |
| 0.1238        | 2.9   | 320  | 0.1220          |
| 0.1256        | 2.99  | 330  | 0.1220          |


### Framework versions

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