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V0424HMA11
Litzy619/V0424HMA11
V0424HMA11 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%
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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. -->
V0424HMA11
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: 0.1412
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 |
|---|---|---|---|
| 1.5556 | 0.09 | 10 | 0.1548 |
| 0.1468 | 0.18 | 20 | 0.1143 |
| 0.11 | 0.27 | 30 | 0.0864 |
| 0.0934 | 0.36 | 40 | 0.0842 |
| 0.0847 | 0.45 | 50 | 0.0936 |
| 0.0912 | 0.54 | 60 | 0.0792 |
| 0.0786 | 0.63 | 70 | 0.0725 |
| 0.083 | 0.73 | 80 | 0.0987 |
| 0.0934 | 0.82 | 90 | 0.0826 |
| 0.0934 | 0.91 | 100 | 0.0884 |
| 0.3432 | 1.0 | 110 | 0.0989 |
| 0.6119 | 1.09 | 120 | 1.4246 |
| 2.0853 | 1.18 | 130 | 0.9385 |
| 2.3314 | 1.27 | 140 | 0.7055 |
| 0.3655 | 1.36 | 150 | 0.1811 |
| 0.2991 | 1.45 | 160 | 0.1788 |
| 0.1823 | 1.54 | 170 | 0.1658 |
| 0.1728 | 1.63 | 180 | 0.1682 |
| 0.1578 | 1.72 | 190 | 0.1532 |
| 0.1573 | 1.81 | 200 | 3.2118 |
| 0.5035 | 1.9 | 210 | 0.1571 |
| 0.1625 | 1.99 | 220 | 0.1573 |
| 0.1639 | 2.08 | 230 | 0.1697 |
| 0.1598 | 2.18 | 240 | 0.1540 |
| 0.1523 | 2.27 | 250 | 0.1510 |
| 0.1528 | 2.36 | 260 | 0.1497 |
| 0.1485 | 2.45 | 270 | 0.1491 |
| 0.1504 | 2.54 | 280 | 0.1443 |
| 0.1436 | 2.63 | 290 | 0.1450 |
| 0.1475 | 2.72 | 300 | 0.1421 |
| 0.1452 | 2.81 | 310 | 0.1408 |
| 0.1414 | 2.9 | 320 | 0.1415 |
| 0.1387 | 2.99 | 330 | 0.1412 |
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