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V0417MADP3
Litzy619/V0417MADP3
V0417MADP3 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 18, 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. -->
V0417MADP3
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: 0.1901
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 |
|---|---|---|---|
| 8.5507 | 0.09 | 10 | 3.0786 |
| 6.3727 | 0.18 | 20 | 2.6464 |
| 3.4656 | 0.27 | 30 | 1.9120 |
| 1.5044 | 0.36 | 40 | 1.1144 |
| 0.581 | 0.45 | 50 | 0.7389 |
| 0.3434 | 0.54 | 60 | 0.5960 |
| 0.3386 | 0.63 | 70 | 0.5215 |
| 0.2957 | 0.73 | 80 | 0.5323 |
| 0.258 | 0.82 | 90 | 0.4773 |
| 0.263 | 0.91 | 100 | 0.4986 |
| 0.2584 | 1.0 | 110 | 0.4831 |
| 0.2808 | 1.09 | 120 | 0.5051 |
| 0.2978 | 1.18 | 130 | 0.4790 |
| 0.2479 | 1.27 | 140 | 0.4456 |
| 0.4023 | 1.36 | 150 | 0.4223 |
| 0.21 | 1.45 | 160 | 0.2159 |
| 0.1788 | 1.54 | 170 | 0.2052 |
| 0.1786 | 1.63 | 180 | 0.2024 |
| 0.1748 | 1.72 | 190 | 0.2013 |
| 0.1718 | 1.81 | 200 | 0.2138 |
| 0.176 | 1.9 | 210 | 0.2197 |
| 0.173 | 1.99 | 220 | 0.2321 |
| 0.1877 | 2.08 | 230 | 0.2317 |
| 0.1732 | 2.18 | 240 | 0.2126 |
| 0.1661 | 2.27 | 250 | 0.1958 |
| 0.1668 | 2.36 | 260 | 0.1955 |
| 0.1642 | 2.45 | 270 | 0.1957 |
| 0.1612 | 2.54 | 280 | 0.1937 |
| 0.1681 | 2.63 | 290 | 0.1910 |
| 0.1622 | 2.72 | 300 | 0.1901 |
| 0.1592 | 2.81 | 310 | 0.1898 |
| 0.1657 | 2.9 | 320 | 0.1904 |
| 0.1696 | 2.99 | 330 | 0.1901 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 17, 2024
- Updated
- Apr 18, 2024