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PHI30512HMAB16H
Litzy619/PHI30512HMAB16H
PHI30512HMAB16H 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 May 13, 2024
Parameters
3.9B
8.2 GB on disk
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.safetensors7.9 GB · 96%
Parameter types
How the weights are stored.
BF163.8B · 99%
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. -->
PHI30512HMAB16H
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1633
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 |
|---|---|---|---|
| 4.7915 | 0.09 | 10 | 1.7498 |
| 0.9756 | 0.18 | 20 | 0.2822 |
| 0.2692 | 0.27 | 30 | 0.2313 |
| 0.2426 | 0.36 | 40 | 0.2245 |
| 0.2219 | 0.45 | 50 | 0.2097 |
| 0.2025 | 0.54 | 60 | 0.2170 |
| 0.2107 | 0.63 | 70 | 0.2090 |
| 0.2164 | 0.73 | 80 | 0.2058 |
| 0.1826 | 0.82 | 90 | 0.1733 |
| 0.1676 | 0.91 | 100 | 0.1635 |
| 0.2174 | 1.0 | 110 | 0.1705 |
| 0.165 | 1.09 | 120 | 0.1654 |
| 0.1654 | 1.18 | 130 | 0.1675 |
| 0.1758 | 1.27 | 140 | 0.1648 |
| 0.1669 | 1.36 | 150 | 0.1644 |
| 0.161 | 1.45 | 160 | 0.1656 |
| 0.1644 | 1.54 | 170 | 0.1633 |
| 0.1635 | 1.63 | 180 | 0.1627 |
| 0.1641 | 1.72 | 190 | 0.1680 |
| 0.1642 | 1.81 | 200 | 0.1642 |
| 0.1656 | 1.9 | 210 | 0.1636 |
| 0.1625 | 1.99 | 220 | 0.1648 |
| 0.1635 | 2.08 | 230 | 0.1633 |
| 0.1606 | 2.18 | 240 | 0.1627 |
| 0.1597 | 2.27 | 250 | 0.1631 |
| 0.1625 | 2.36 | 260 | 0.1636 |
| 0.161 | 2.45 | 270 | 0.1635 |
| 0.1613 | 2.54 | 280 | 0.1638 |
| 0.1615 | 2.63 | 290 | 0.1639 |
| 0.1628 | 2.72 | 300 | 0.1636 |
| 0.163 | 2.81 | 310 | 0.1634 |
| 0.1617 | 2.9 | 320 | 0.1633 |
| 0.166 | 2.99 | 330 | 0.1633 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- mit
- Created
- May 13, 2024
- Updated
- May 13, 2024