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Phi0503HMA6
Litzy619/Phi0503HMA6
Phi0503HMA6 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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Public
Updated May 6, 2024
Parameters
3.9B
8.4 GB on disk
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.safetensors7.9 GB · 95%
Parameter types
How the weights are stored.
BF163.8B · 98%
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. -->
Phi0503HMA6
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: 0.1670
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 |
|---|---|---|---|
| 4.2469 | 0.09 | 10 | 0.9109 |
| 0.4285 | 0.18 | 20 | 0.2506 |
| 0.266 | 0.27 | 30 | 0.2427 |
| 0.2313 | 0.36 | 40 | 0.2118 |
| 0.1808 | 0.45 | 50 | 0.1604 |
| 0.163 | 0.54 | 60 | 0.1760 |
| 0.2571 | 0.63 | 70 | 0.1448 |
| 0.2789 | 0.73 | 80 | 0.1488 |
| 0.7096 | 0.82 | 90 | 1.2197 |
| 1.051 | 0.91 | 100 | 1.2133 |
| 0.4623 | 1.0 | 110 | 4.9980 |
| 4.8479 | 1.09 | 120 | 2.3085 |
| 1.6873 | 1.18 | 130 | 0.7471 |
| 0.5896 | 1.27 | 140 | 0.3693 |
| 0.334 | 1.36 | 150 | 0.2707 |
| 0.2556 | 1.45 | 160 | 0.2347 |
| 0.2087 | 1.54 | 170 | 0.1840 |
| 0.187 | 1.63 | 180 | 0.1858 |
| 0.1833 | 1.72 | 190 | 0.1842 |
| 0.1755 | 1.81 | 200 | 0.1787 |
| 0.1772 | 1.9 | 210 | 0.1708 |
| 0.1698 | 1.99 | 220 | 0.1714 |
| 0.1723 | 2.08 | 230 | 0.1691 |
| 0.1674 | 2.18 | 240 | 0.1693 |
| 0.1682 | 2.27 | 250 | 0.1709 |
| 0.1684 | 2.36 | 260 | 0.1702 |
| 0.166 | 2.45 | 270 | 0.1681 |
| 0.1651 | 2.54 | 280 | 0.1683 |
| 0.1689 | 2.63 | 290 | 0.1688 |
| 0.17 | 2.72 | 300 | 0.1675 |
| 0.1696 | 2.81 | 310 | 0.1674 |
| 0.1663 | 2.9 | 320 | 0.1670 |
| 0.1712 | 2.99 | 330 | 0.1670 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- mit
- Created
- May 6, 2024
- Updated
- May 6, 2024