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G0515HMA6H
Litzy619/G0515HMA6H
G0515HMA6H 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
- f021ff09
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. -->
G0515HMA6H
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: 0.1180
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 |
|---|---|---|---|
| 3.1941 | 0.09 | 10 | 2.8283 |
| 2.6444 | 0.18 | 20 | 2.1939 |
| 1.7247 | 0.27 | 30 | 1.1322 |
| 0.7165 | 0.36 | 40 | 0.3005 |
| 0.2156 | 0.45 | 50 | 0.1657 |
| 0.1572 | 0.54 | 60 | 0.1568 |
| 0.1515 | 0.63 | 70 | 0.1527 |
| 0.1523 | 0.73 | 80 | 0.1499 |
| 0.1426 | 0.82 | 90 | 0.1632 |
| 0.1518 | 0.91 | 100 | 0.1495 |
| 0.1522 | 1.0 | 110 | 0.1534 |
| 0.1452 | 1.09 | 120 | 0.1495 |
| 0.1462 | 1.18 | 130 | 0.1488 |
| 0.1462 | 1.27 | 140 | 0.1465 |
| 0.1478 | 1.36 | 150 | 0.1458 |
| 0.1419 | 1.45 | 160 | 0.1467 |
| 0.1422 | 1.54 | 170 | 0.1435 |
| 0.1448 | 1.63 | 180 | 0.1418 |
| 0.1424 | 1.72 | 190 | 0.1410 |
| 0.1371 | 1.81 | 200 | 0.1324 |
| 0.1365 | 1.9 | 210 | 0.1360 |
| 0.1326 | 1.99 | 220 | 0.1256 |
| 0.1254 | 2.08 | 230 | 0.1266 |
| 0.1261 | 2.18 | 240 | 0.1270 |
| 0.1241 | 2.27 | 250 | 0.1260 |
| 0.1259 | 2.36 | 260 | 0.1243 |
| 0.1245 | 2.45 | 270 | 0.1225 |
| 0.1207 | 2.54 | 280 | 0.1215 |
| 0.1177 | 2.63 | 290 | 0.1193 |
| 0.1168 | 2.72 | 300 | 0.1182 |
| 0.1198 | 2.81 | 310 | 0.1181 |
| 0.1196 | 2.9 | 320 | 0.1181 |
| 0.1199 | 2.99 | 330 | 0.1180 |
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