Downloads · 30 days
0
G0428B2
Litzy619/G0428B2
G0428B2 is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as gemma.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated Apr 29, 2024
Parameters
2.5B
20.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors10.1 GB · 100%
At a glance
- License
- gemma
- Access
- Public
- Created
- Apr 28, 2024
- Updated
- Apr 29, 2024
- SHA
- d6bd9d8e
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
G0428B2
This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1291
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2513 | 0.09 | 10 | 1.9189 |
| 1.9252 | 0.18 | 20 | 1.9019 |
| 1.8761 | 0.27 | 30 | 1.7972 |
| 1.7045 | 0.36 | 40 | 1.5332 |
| 1.348 | 0.45 | 50 | 1.0846 |
| 0.9036 | 0.54 | 60 | 0.4970 |
| 0.3466 | 0.63 | 70 | 0.2054 |
| 0.1888 | 0.73 | 80 | 0.1562 |
| 0.1458 | 0.82 | 90 | 0.1490 |
| 0.1531 | 0.91 | 100 | 0.1478 |
| 0.1561 | 1.0 | 110 | 0.1477 |
| 0.142 | 1.09 | 120 | 0.1474 |
| 0.1687 | 1.18 | 130 | 0.1463 |
| 0.1426 | 1.27 | 140 | 0.1451 |
| 0.1577 | 1.36 | 150 | 0.1434 |
| 0.1386 | 1.45 | 160 | 0.1419 |
| 0.136 | 1.54 | 170 | 0.1397 |
| 0.135 | 1.63 | 180 | 0.1385 |
| 0.1489 | 1.72 | 190 | 0.1377 |
| 0.146 | 1.81 | 200 | 0.1349 |
| 0.1367 | 1.9 | 210 | 0.1340 |
| 0.1347 | 1.99 | 220 | 0.1338 |
| 0.1317 | 2.08 | 230 | 0.1318 |
| 0.1554 | 2.18 | 240 | 0.1309 |
| 0.1285 | 2.27 | 250 | 0.1308 |
| 0.1328 | 2.36 | 260 | 0.1310 |
| 0.1354 | 2.45 | 270 | 0.1305 |
| 0.1324 | 2.54 | 280 | 0.1301 |
| 0.1362 | 2.63 | 290 | 0.1297 |
| 0.1257 | 2.72 | 300 | 0.1293 |
| 0.1274 | 2.81 | 310 | 0.1291 |
| 0.1472 | 2.9 | 320 | 0.1291 |
| 0.1405 | 2.99 | 330 | 0.1291 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- gemma
- Created
- Apr 28, 2024
- Updated
- Apr 29, 2024