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G0515HMA19H
Litzy619/G0515HMA19H
G0515HMA19H 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 16, 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 16, 2024
- SHA
- 83a4e5ea
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. -->
G0515HMA19H
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: 0.1160
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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.1518 | 0.09 | 10 | 2.7265 |
| 2.3626 | 0.18 | 20 | 1.7120 |
| 1.1521 | 0.27 | 30 | 0.4848 |
| 0.2787 | 0.36 | 40 | 0.1659 |
| 0.1579 | 0.45 | 50 | 0.1578 |
| 0.1514 | 0.54 | 60 | 0.1504 |
| 0.1494 | 0.63 | 70 | 0.1482 |
| 0.1508 | 0.73 | 80 | 0.1493 |
| 0.1424 | 0.82 | 90 | 0.1489 |
| 0.1462 | 0.91 | 100 | 0.1487 |
| 0.1488 | 1.0 | 110 | 0.1490 |
| 0.1437 | 1.09 | 120 | 0.1487 |
| 0.1442 | 1.18 | 130 | 0.1478 |
| 0.1452 | 1.27 | 140 | 0.1454 |
| 0.1461 | 1.36 | 150 | 0.1444 |
| 0.1388 | 1.45 | 160 | 0.1444 |
| 0.142 | 1.54 | 170 | 0.1423 |
| 0.1409 | 1.63 | 180 | 0.1399 |
| 0.1421 | 1.72 | 190 | 0.1402 |
| 0.1347 | 1.81 | 200 | 0.1334 |
| 0.1356 | 1.9 | 210 | 0.1298 |
| 0.1296 | 1.99 | 220 | 0.1266 |
| 0.1237 | 2.08 | 230 | 0.1263 |
| 0.1214 | 2.18 | 240 | 0.1242 |
| 0.1185 | 2.27 | 250 | 0.1227 |
| 0.1238 | 2.36 | 260 | 0.1216 |
| 0.1226 | 2.45 | 270 | 0.1207 |
| 0.1156 | 2.54 | 280 | 0.1196 |
| 0.1111 | 2.63 | 290 | 0.1177 |
| 0.1128 | 2.72 | 300 | 0.1166 |
| 0.1154 | 2.81 | 310 | 0.1161 |
| 0.1165 | 2.9 | 320 | 0.1160 |
| 0.1172 | 2.99 | 330 | 0.1160 |
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 16, 2024