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---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0513HMA6H
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. -->
# G0513HMA6H
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: 0.1240
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.161 | 0.09 | 10 | 2.8226 |
| 2.4808 | 0.18 | 20 | 1.9257 |
| 1.4989 | 0.27 | 30 | 0.9749 |
| 0.6093 | 0.36 | 40 | 0.2572 |
| 0.1925 | 0.45 | 50 | 0.1591 |
| 0.1558 | 0.54 | 60 | 0.1523 |
| 0.1517 | 0.63 | 70 | 0.1497 |
| 0.1503 | 0.73 | 80 | 0.1487 |
| 0.1422 | 0.82 | 90 | 0.1499 |
| 0.1459 | 0.91 | 100 | 0.1487 |
| 0.1494 | 1.0 | 110 | 0.1495 |
| 0.1438 | 1.09 | 120 | 0.1499 |
| 0.1458 | 1.18 | 130 | 0.1472 |
| 0.1465 | 1.27 | 140 | 0.1463 |
| 0.1483 | 1.36 | 150 | 0.1464 |
| 0.1426 | 1.45 | 160 | 0.1480 |
| 0.1433 | 1.54 | 170 | 0.1450 |
| 0.1443 | 1.63 | 180 | 0.1440 |
| 0.1455 | 1.72 | 190 | 0.1495 |
| 0.1437 | 1.81 | 200 | 0.1439 |
| 0.1433 | 1.9 | 210 | 0.1398 |
| 0.1408 | 1.99 | 220 | 0.1387 |
| 0.1348 | 2.08 | 230 | 0.1340 |
| 0.1311 | 2.18 | 240 | 0.1334 |
| 0.1303 | 2.27 | 250 | 0.1297 |
| 0.1319 | 2.36 | 260 | 0.1285 |
| 0.1297 | 2.45 | 270 | 0.1291 |
| 0.129 | 2.54 | 280 | 0.1270 |
| 0.1247 | 2.63 | 290 | 0.1252 |
| 0.1251 | 2.72 | 300 | 0.1242 |
| 0.1299 | 2.81 | 310 | 0.1239 |
| 0.1271 | 2.9 | 320 | 0.1240 |
| 0.1269 | 2.99 | 330 | 0.1240 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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