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---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0428HMA8
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. -->
# G0428HMA8
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: 0.1108
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7848 | 0.09 | 10 | 2.0338 |
| 1.5344 | 0.18 | 20 | 0.9449 |
| 0.5532 | 0.27 | 30 | 0.2231 |
| 0.1757 | 0.36 | 40 | 0.1577 |
| 0.151 | 0.45 | 50 | 0.1493 |
| 0.149 | 0.54 | 60 | 0.1492 |
| 0.1476 | 0.63 | 70 | 0.1472 |
| 0.1488 | 0.73 | 80 | 0.1479 |
| 0.1416 | 0.82 | 90 | 0.1485 |
| 0.1452 | 0.91 | 100 | 0.1475 |
| 0.1484 | 1.0 | 110 | 0.1486 |
| 0.1431 | 1.09 | 120 | 0.1476 |
| 0.1447 | 1.18 | 130 | 0.1481 |
| 0.1451 | 1.27 | 140 | 0.1469 |
| 0.1474 | 1.36 | 150 | 0.1455 |
| 0.1417 | 1.45 | 160 | 0.1463 |
| 0.1428 | 1.54 | 170 | 0.1426 |
| 0.1406 | 1.63 | 180 | 0.1370 |
| 0.1392 | 1.72 | 190 | 0.1435 |
| 0.1355 | 1.81 | 200 | 0.1343 |
| 0.1343 | 1.9 | 210 | 0.1318 |
| 0.1297 | 1.99 | 220 | 0.1237 |
| 0.1205 | 2.08 | 230 | 0.1239 |
| 0.1161 | 2.18 | 240 | 0.1210 |
| 0.1139 | 2.27 | 250 | 0.1177 |
| 0.1159 | 2.36 | 260 | 0.1159 |
| 0.1165 | 2.45 | 270 | 0.1150 |
| 0.111 | 2.54 | 280 | 0.1146 |
| 0.1049 | 2.63 | 290 | 0.1129 |
| 0.1055 | 2.72 | 300 | 0.1116 |
| 0.1108 | 2.81 | 310 | 0.1112 |
| 0.1117 | 2.9 | 320 | 0.1109 |
| 0.1116 | 2.99 | 330 | 0.1108 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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