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V0417MAD4
Litzy619/V0417MAD4
V0417MAD4 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 Apr 17, 2024
Parameters
2.8B
6.1 GB on disk
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.safetensors5.8 GB · 96%
Parameter types
How the weights are stored.
F162.8B · 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. -->
V0417MAD4
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: 0.0612
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 |
|---|---|---|---|
| 2.3012 | 0.09 | 10 | 1.4007 |
| 0.8855 | 0.18 | 20 | 0.1411 |
| 0.1305 | 0.27 | 30 | 0.0948 |
| 0.1056 | 0.36 | 40 | 0.0843 |
| 0.089 | 0.45 | 50 | 0.0791 |
| 0.0916 | 0.54 | 60 | 0.0735 |
| 0.0802 | 0.63 | 70 | 0.0706 |
| 0.0754 | 0.73 | 80 | 0.0730 |
| 0.0811 | 0.82 | 90 | 0.0663 |
| 0.0754 | 0.91 | 100 | 0.0663 |
| 0.0734 | 1.0 | 110 | 0.0662 |
| 0.0675 | 1.09 | 120 | 0.0623 |
| 0.0704 | 1.18 | 130 | 0.0689 |
| 0.0652 | 1.27 | 140 | 0.0663 |
| 0.0621 | 1.36 | 150 | 0.0666 |
| 0.0715 | 1.45 | 160 | 0.0634 |
| 0.0641 | 1.54 | 170 | 0.0655 |
| 0.0693 | 1.63 | 180 | 0.0607 |
| 0.1132 | 1.72 | 190 | 0.0714 |
| 0.0824 | 1.81 | 200 | 0.0726 |
| 0.0696 | 1.9 | 210 | 0.0682 |
| 0.0641 | 1.99 | 220 | 0.0647 |
| 0.0568 | 2.08 | 230 | 0.0660 |
| 0.0628 | 2.18 | 240 | 0.0623 |
| 0.0608 | 2.27 | 250 | 0.0614 |
| 0.0593 | 2.36 | 260 | 0.0647 |
| 0.0609 | 2.45 | 270 | 0.0612 |
| 0.0558 | 2.54 | 280 | 0.0615 |
| 0.0539 | 2.63 | 290 | 0.0621 |
| 0.0582 | 2.72 | 300 | 0.0616 |
| 0.0632 | 2.81 | 310 | 0.0613 |
| 0.0535 | 2.9 | 320 | 0.0612 |
| 0.0591 | 2.99 | 330 | 0.0612 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 17, 2024
- Updated
- Apr 17, 2024