Downloads · 30 days
0
G0428HMA26
Litzy619/G0428HMA26
G0428HMA26 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
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 29, 2024
- SHA
- de36dde0
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. -->
G0428HMA26
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: 0.1123
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 |
|---|---|---|---|
| 2.48 | 0.09 | 10 | 1.3998 |
| 0.7559 | 0.18 | 20 | 0.2139 |
| 0.1722 | 0.27 | 30 | 0.1588 |
| 0.1516 | 0.36 | 40 | 0.1510 |
| 0.1466 | 0.45 | 50 | 0.1478 |
| 0.1473 | 0.54 | 60 | 0.1488 |
| 0.148 | 0.63 | 70 | 0.1479 |
| 0.1505 | 0.73 | 80 | 0.1491 |
| 0.1423 | 0.82 | 90 | 0.1494 |
| 0.1466 | 0.91 | 100 | 0.1490 |
| 0.1486 | 1.0 | 110 | 0.1487 |
| 0.1603 | 1.09 | 120 | 0.1975 |
| 0.298 | 1.18 | 130 | 0.6268 |
| 0.362 | 1.27 | 140 | 0.1486 |
| 0.1493 | 1.36 | 150 | 0.1485 |
| 0.1402 | 1.45 | 160 | 0.1469 |
| 0.1442 | 1.54 | 170 | 0.1431 |
| 0.1346 | 1.63 | 180 | 0.1396 |
| 0.1405 | 1.72 | 190 | 0.1378 |
| 0.132 | 1.81 | 200 | 0.1358 |
| 0.1309 | 1.9 | 210 | 0.1311 |
| 0.1266 | 1.99 | 220 | 0.1243 |
| 0.119 | 2.08 | 230 | 0.1219 |
| 0.1183 | 2.18 | 240 | 0.1208 |
| 0.114 | 2.27 | 250 | 0.1188 |
| 0.1129 | 2.36 | 260 | 0.1212 |
| 0.1152 | 2.45 | 270 | 0.1179 |
| 0.105 | 2.54 | 280 | 0.1157 |
| 0.106 | 2.63 | 290 | 0.1125 |
| 0.1033 | 2.72 | 300 | 0.1127 |
| 0.1074 | 2.81 | 310 | 0.1123 |
| 0.1098 | 2.9 | 320 | 0.1123 |
| 0.1091 | 2.99 | 330 | 0.1123 |
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