Downloads · 30 days
0
G0428HMA2
Litzy619/G0428HMA2
G0428HMA2 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 28, 2024
Parameters
2.5B
10.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors10.1 GB · 98%
At a glance
- License
- gemma
- Access
- Public
- Created
- Apr 28, 2024
- Updated
- Apr 28, 2024
- SHA
- c7aa6be6
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. -->
G0428HMA2
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: 0.1085
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 |
|---|---|---|---|
| 2.7283 | 0.09 | 10 | 1.9180 |
| 1.3514 | 0.18 | 20 | 0.6885 |
| 0.3688 | 0.27 | 30 | 0.1812 |
| 0.1614 | 0.36 | 40 | 0.1524 |
| 0.1477 | 0.45 | 50 | 0.1476 |
| 0.1475 | 0.54 | 60 | 0.1480 |
| 0.1477 | 0.63 | 70 | 0.1475 |
| 0.1481 | 0.73 | 80 | 0.1481 |
| 0.1415 | 0.82 | 90 | 0.1487 |
| 0.1455 | 0.91 | 100 | 0.1473 |
| 0.1484 | 1.0 | 110 | 0.1482 |
| 0.143 | 1.09 | 120 | 0.1482 |
| 0.1441 | 1.18 | 130 | 0.1479 |
| 0.1452 | 1.27 | 140 | 0.1453 |
| 0.1464 | 1.36 | 150 | 0.1433 |
| 0.1394 | 1.45 | 160 | 0.1517 |
| 0.1425 | 1.54 | 170 | 0.1415 |
| 0.1378 | 1.63 | 180 | 0.1336 |
| 0.1322 | 1.72 | 190 | 0.1349 |
| 0.1269 | 1.81 | 200 | 0.1243 |
| 0.1255 | 1.9 | 210 | 0.1209 |
| 0.1212 | 1.99 | 220 | 0.1208 |
| 0.1115 | 2.08 | 230 | 0.1180 |
| 0.1151 | 2.18 | 240 | 0.1169 |
| 0.1089 | 2.27 | 250 | 0.1160 |
| 0.1085 | 2.36 | 260 | 0.1134 |
| 0.1099 | 2.45 | 270 | 0.1118 |
| 0.1031 | 2.54 | 280 | 0.1112 |
| 0.0986 | 2.63 | 290 | 0.1099 |
| 0.1008 | 2.72 | 300 | 0.1091 |
| 0.1075 | 2.81 | 310 | 0.1087 |
| 0.1048 | 2.9 | 320 | 0.1085 |
| 0.1047 | 2.99 | 330 | 0.1085 |
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 28, 2024