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G0515HMA24H
Litzy619/G0515HMA24H
G0515HMA24H 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. --
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Public
Updated May 15, 2024
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10.2 GB on disk
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At a glance
- License
- gemma
- Access
- Public
- Created
- May 15, 2024
- Updated
- May 15, 2024
- SHA
- 511f9111
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. -->
G0515HMA24H
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: 0.1169
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 |
|---|---|---|---|
| 3.171 | 0.09 | 10 | 2.7380 |
| 2.343 | 0.18 | 20 | 1.7302 |
| 1.2081 | 0.27 | 30 | 0.5724 |
| 0.3215 | 0.36 | 40 | 0.1716 |
| 0.1576 | 0.45 | 50 | 0.1560 |
| 0.1519 | 0.54 | 60 | 0.1512 |
| 0.1491 | 0.63 | 70 | 0.1486 |
| 0.1507 | 0.73 | 80 | 0.1504 |
| 0.1428 | 0.82 | 90 | 0.1496 |
| 0.1455 | 0.91 | 100 | 0.1486 |
| 0.1485 | 1.0 | 110 | 0.1495 |
| 0.1441 | 1.09 | 120 | 0.1485 |
| 0.1456 | 1.18 | 130 | 0.1489 |
| 0.1458 | 1.27 | 140 | 0.1466 |
| 0.1484 | 1.36 | 150 | 0.1462 |
| 0.1424 | 1.45 | 160 | 0.1481 |
| 0.1426 | 1.54 | 170 | 0.1445 |
| 0.1447 | 1.63 | 180 | 0.1424 |
| 0.1448 | 1.72 | 190 | 0.1439 |
| 0.1398 | 1.81 | 200 | 0.1396 |
| 0.1386 | 1.9 | 210 | 0.1333 |
| 0.133 | 1.99 | 220 | 0.1277 |
| 0.1266 | 2.08 | 230 | 0.1289 |
| 0.126 | 2.18 | 240 | 0.1236 |
| 0.1222 | 2.27 | 250 | 0.1262 |
| 0.1248 | 2.36 | 260 | 0.1237 |
| 0.1217 | 2.45 | 270 | 0.1209 |
| 0.1197 | 2.54 | 280 | 0.1205 |
| 0.1155 | 2.63 | 290 | 0.1188 |
| 0.1123 | 2.72 | 300 | 0.1175 |
| 0.1195 | 2.81 | 310 | 0.1171 |
| 0.1192 | 2.9 | 320 | 0.1169 |
| 0.1166 | 2.99 | 330 | 0.1169 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- gemma
- Created
- May 15, 2024
- Updated
- May 15, 2024