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---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0513HMA4H
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. -->
# G0513HMA4H
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: 0.1331
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.1824 | 0.09 | 10 | 2.8991 |
| 2.6535 | 0.18 | 20 | 2.2337 |
| 1.8658 | 0.27 | 30 | 1.4097 |
| 1.0771 | 0.36 | 40 | 0.6675 |
| 0.4164 | 0.45 | 50 | 0.2215 |
| 0.1854 | 0.54 | 60 | 0.1678 |
| 0.1586 | 0.63 | 70 | 0.1549 |
| 0.153 | 0.73 | 80 | 0.1504 |
| 0.1434 | 0.82 | 90 | 0.1510 |
| 0.1463 | 0.91 | 100 | 0.1488 |
| 0.1487 | 1.0 | 110 | 0.1499 |
| 0.1439 | 1.09 | 120 | 0.1488 |
| 0.1454 | 1.18 | 130 | 0.1481 |
| 0.1456 | 1.27 | 140 | 0.1468 |
| 0.148 | 1.36 | 150 | 0.1459 |
| 0.1426 | 1.45 | 160 | 0.1489 |
| 0.1441 | 1.54 | 170 | 0.1468 |
| 0.1447 | 1.63 | 180 | 0.1448 |
| 0.1456 | 1.72 | 190 | 0.1494 |
| 0.1454 | 1.81 | 200 | 0.1461 |
| 0.1448 | 1.9 | 210 | 0.1451 |
| 0.1454 | 1.99 | 220 | 0.1436 |
| 0.1406 | 2.08 | 230 | 0.1407 |
| 0.136 | 2.18 | 240 | 0.1395 |
| 0.1345 | 2.27 | 250 | 0.1406 |
| 0.1392 | 2.36 | 260 | 0.1384 |
| 0.1356 | 2.45 | 270 | 0.1367 |
| 0.1343 | 2.54 | 280 | 0.1357 |
| 0.1313 | 2.63 | 290 | 0.1344 |
| 0.13 | 2.72 | 300 | 0.1331 |
| 0.1356 | 2.81 | 310 | 0.1330 |
| 0.1338 | 2.9 | 320 | 0.1330 |
| 0.1323 | 2.99 | 330 | 0.1331 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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