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---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0515HMA7H
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. -->
# G0515HMA7H
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: 0.1387
## 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2373 | 0.09 | 10 | 3.0159 |
| 2.8088 | 0.18 | 20 | 2.4522 |
| 2.1245 | 0.27 | 30 | 1.6991 |
| 1.3384 | 0.36 | 40 | 0.9299 |
| 0.6218 | 0.45 | 50 | 0.3077 |
| 0.2261 | 0.54 | 60 | 0.1709 |
| 0.1623 | 0.63 | 70 | 0.1570 |
| 0.158 | 0.73 | 80 | 0.1547 |
| 0.1461 | 0.82 | 90 | 0.1521 |
| 0.1467 | 0.91 | 100 | 0.1487 |
| 0.149 | 1.0 | 110 | 0.1501 |
| 0.1444 | 1.09 | 120 | 0.1489 |
| 0.1448 | 1.18 | 130 | 0.1481 |
| 0.1457 | 1.27 | 140 | 0.1468 |
| 0.1484 | 1.36 | 150 | 0.1464 |
| 0.1425 | 1.45 | 160 | 0.1478 |
| 0.1436 | 1.54 | 170 | 0.1464 |
| 0.1453 | 1.63 | 180 | 0.1450 |
| 0.1465 | 1.72 | 190 | 0.1480 |
| 0.1456 | 1.81 | 200 | 0.1460 |
| 0.1467 | 1.9 | 210 | 0.1462 |
| 0.1471 | 1.99 | 220 | 0.1453 |
| 0.1441 | 2.08 | 230 | 0.1449 |
| 0.1396 | 2.18 | 240 | 0.1442 |
| 0.1412 | 2.27 | 250 | 0.1442 |
| 0.1437 | 2.36 | 260 | 0.1430 |
| 0.1397 | 2.45 | 270 | 0.1430 |
| 0.1384 | 2.54 | 280 | 0.1412 |
| 0.1368 | 2.63 | 290 | 0.1403 |
| 0.1367 | 2.72 | 300 | 0.1391 |
| 0.1384 | 2.81 | 310 | 0.1387 |
| 0.1364 | 2.9 | 320 | 0.1388 |
| 0.1371 | 2.99 | 330 | 0.1387 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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