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G0428HMA22
Litzy619/G0428HMA22
G0428HMA22 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
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10.3 GB on disk
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At a glance
- License
- gemma
- Access
- Public
- Created
- Apr 28, 2024
- Updated
- Apr 29, 2024
- SHA
- 8c7fbdf6
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. -->
G0428HMA22
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: 0.1053
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 |
|---|---|---|---|
| 2.5672 | 0.09 | 10 | 1.5723 |
| 0.95 | 0.18 | 20 | 0.3053 |
| 0.1975 | 0.27 | 30 | 0.1617 |
| 0.1542 | 0.36 | 40 | 0.1482 |
| 0.1465 | 0.45 | 50 | 0.1487 |
| 0.148 | 0.54 | 60 | 0.1489 |
| 0.1482 | 0.63 | 70 | 0.1472 |
| 0.1491 | 0.73 | 80 | 0.1474 |
| 0.1423 | 0.82 | 90 | 0.1480 |
| 0.1448 | 0.91 | 100 | 0.1481 |
| 0.1481 | 1.0 | 110 | 0.1487 |
| 0.1439 | 1.09 | 120 | 0.1480 |
| 0.1453 | 1.18 | 130 | 0.1486 |
| 0.1463 | 1.27 | 140 | 0.1457 |
| 0.1462 | 1.36 | 150 | 0.1437 |
| 0.1372 | 1.45 | 160 | 0.1387 |
| 0.1398 | 1.54 | 170 | 0.1416 |
| 0.133 | 1.63 | 180 | 0.1324 |
| 0.1316 | 1.72 | 190 | 0.1315 |
| 0.1279 | 1.81 | 200 | 0.1283 |
| 0.1273 | 1.9 | 210 | 0.1243 |
| 0.1232 | 1.99 | 220 | 0.1185 |
| 0.1129 | 2.08 | 230 | 0.1186 |
| 0.1112 | 2.18 | 240 | 0.1143 |
| 0.1046 | 2.27 | 250 | 0.1138 |
| 0.1075 | 2.36 | 260 | 0.1122 |
| 0.1088 | 2.45 | 270 | 0.1098 |
| 0.1046 | 2.54 | 280 | 0.1102 |
| 0.0971 | 2.63 | 290 | 0.1084 |
| 0.0994 | 2.72 | 300 | 0.1072 |
| 0.1019 | 2.81 | 310 | 0.1058 |
| 0.1021 | 2.9 | 320 | 0.1054 |
| 0.1068 | 2.99 | 330 | 0.1053 |
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