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---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0513HMAB1
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. -->
# G0513HMAB1
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: 0.1352
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.926 | 0.09 | 10 | 1.9074 |
| 1.8937 | 0.18 | 20 | 1.8418 |
| 1.7669 | 0.27 | 30 | 1.6397 |
| 1.4926 | 0.36 | 40 | 1.2660 |
| 1.0153 | 0.45 | 50 | 0.6891 |
| 0.5171 | 0.54 | 60 | 0.3388 |
| 0.2538 | 0.63 | 70 | 0.1816 |
| 0.1674 | 0.73 | 80 | 0.1558 |
| 0.147 | 0.82 | 90 | 0.1501 |
| 0.1461 | 0.91 | 100 | 0.1470 |
| 0.1485 | 1.0 | 110 | 0.1488 |
| 0.1444 | 1.09 | 120 | 0.1460 |
| 0.1446 | 1.18 | 130 | 0.1469 |
| 0.1459 | 1.27 | 140 | 0.1454 |
| 0.1469 | 1.36 | 150 | 0.1441 |
| 0.1404 | 1.45 | 160 | 0.1456 |
| 0.142 | 1.54 | 170 | 0.1426 |
| 0.1418 | 1.63 | 180 | 0.1418 |
| 0.1429 | 1.72 | 190 | 0.1429 |
| 0.1401 | 1.81 | 200 | 0.1400 |
| 0.1415 | 1.9 | 210 | 0.1392 |
| 0.141 | 1.99 | 220 | 0.1395 |
| 0.1393 | 2.08 | 230 | 0.1376 |
| 0.137 | 2.18 | 240 | 0.1374 |
| 0.1349 | 2.27 | 250 | 0.1368 |
| 0.1392 | 2.36 | 260 | 0.1367 |
| 0.1369 | 2.45 | 270 | 0.1364 |
| 0.1337 | 2.54 | 280 | 0.1360 |
| 0.1322 | 2.63 | 290 | 0.1356 |
| 0.1341 | 2.72 | 300 | 0.1353 |
| 0.1349 | 2.81 | 310 | 0.1352 |
| 0.1343 | 2.9 | 320 | 0.1352 |
| 0.1365 | 2.99 | 330 | 0.1352 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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