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V0424HMA10
Litzy619/V0424HMA10
V0424HMA10 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 mit.
should probably proofread and complete it, then remove this comment. --
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Updated Apr 25, 2024
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2.9B
6.5 GB on disk
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.safetensors5.9 GB · 91%
Parameter types
How the weights are stored.
F162.8B · 97%
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. -->
V0424HMA10
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1353
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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9203 | 0.09 | 10 | 0.5860 |
| 0.216 | 0.18 | 20 | 0.1276 |
| 0.1187 | 0.27 | 30 | 0.1089 |
| 0.1066 | 0.36 | 40 | 0.0864 |
| 0.0822 | 0.45 | 50 | 0.0775 |
| 0.0891 | 0.54 | 60 | 0.0866 |
| 0.0867 | 0.63 | 70 | 0.0769 |
| 0.0772 | 0.73 | 80 | 0.0991 |
| 0.0862 | 0.82 | 90 | 0.1365 |
| 4.6622 | 0.91 | 100 | 3.8668 |
| 1.4048 | 1.0 | 110 | 0.7169 |
| 0.5278 | 1.09 | 120 | 0.3863 |
| 0.3475 | 1.18 | 130 | 0.3058 |
| 0.2901 | 1.27 | 140 | 0.2546 |
| 0.2383 | 1.36 | 150 | 0.2151 |
| 0.1965 | 1.45 | 160 | 0.1826 |
| 0.1841 | 1.54 | 170 | 0.1697 |
| 0.1713 | 1.63 | 180 | 0.1678 |
| 0.1713 | 1.72 | 190 | 0.2457 |
| 0.1698 | 1.81 | 200 | 0.1620 |
| 0.1594 | 1.9 | 210 | 0.1489 |
| 0.1532 | 1.99 | 220 | 0.1470 |
| 0.1478 | 2.08 | 230 | 0.1530 |
| 0.1418 | 2.18 | 240 | 0.1405 |
| 0.1398 | 2.27 | 250 | 0.1367 |
| 0.1399 | 2.36 | 260 | 0.1384 |
| 0.1343 | 2.45 | 270 | 0.1368 |
| 0.1352 | 2.54 | 280 | 0.1354 |
| 0.1321 | 2.63 | 290 | 0.1372 |
| 0.1342 | 2.72 | 300 | 0.1354 |
| 0.1407 | 2.81 | 310 | 0.1351 |
| 0.1344 | 2.9 | 320 | 0.1352 |
| 0.1328 | 2.99 | 330 | 0.1353 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 24, 2024
- Updated
- Apr 25, 2024