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V0417MADP8
Litzy619/V0417MADP8
V0417MADP8 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.
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Public
Updated Apr 19, 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. -->
V0417MADP8
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: 0.0671
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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.4354 | 0.09 | 10 | 2.6496 |
| 4.1578 | 0.18 | 20 | 1.5199 |
| 2.23 | 0.27 | 30 | 0.1826 |
| 0.884 | 0.36 | 40 | 0.1456 |
| 0.1889 | 0.45 | 50 | 0.1308 |
| 0.1501 | 0.54 | 60 | 0.1216 |
| 0.1389 | 0.63 | 70 | 0.1104 |
| 0.1173 | 0.73 | 80 | 0.1018 |
| 0.1086 | 0.82 | 90 | 0.0899 |
| 0.0966 | 0.91 | 100 | 0.0814 |
| 0.098 | 1.0 | 110 | 0.0814 |
| 0.093 | 1.09 | 120 | 0.0846 |
| 0.093 | 1.18 | 130 | 0.0811 |
| 0.091 | 1.27 | 140 | 0.0782 |
| 0.0858 | 1.36 | 150 | 0.0767 |
| 0.0853 | 1.45 | 160 | 0.0817 |
| 0.089 | 1.54 | 170 | 0.0804 |
| 0.0854 | 1.63 | 180 | 0.0751 |
| 0.0841 | 1.72 | 190 | 0.0766 |
| 0.0843 | 1.81 | 200 | 0.0722 |
| 0.0763 | 1.9 | 210 | 0.0706 |
| 0.0778 | 1.99 | 220 | 0.0707 |
| 0.0712 | 2.08 | 230 | 0.0697 |
| 0.066 | 2.18 | 240 | 0.0691 |
| 0.0687 | 2.27 | 250 | 0.0711 |
| 0.0714 | 2.36 | 260 | 0.0695 |
| 0.0685 | 2.45 | 270 | 0.0692 |
| 0.0648 | 2.54 | 280 | 0.0688 |
| 0.0645 | 2.63 | 290 | 0.0675 |
| 0.0668 | 2.72 | 300 | 0.0670 |
| 0.0665 | 2.81 | 310 | 0.0672 |
| 0.0628 | 2.9 | 320 | 0.0671 |
| 0.0736 | 2.99 | 330 | 0.0671 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 18, 2024
- Updated
- Apr 19, 2024