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0503LayerAnalysis31
Litzy619/0503LayerAnalysis31
0503LayerAnalysis31 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 4, 2024
Repo size
100 MB
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At a glance
- License
- mit
- Access
- Public
- Created
- May 4, 2024
- Updated
- May 4, 2024
- SHA
- 37d7252e
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. -->
0503LayerAnalysis31
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: 0.0564
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 |
|---|---|---|---|
| 2.066 | 0.09 | 10 | 0.9101 |
| 0.2987 | 0.18 | 20 | 0.1450 |
| 0.1452 | 0.27 | 30 | 0.1357 |
| 0.142 | 0.36 | 40 | 0.1149 |
| 0.1195 | 0.45 | 50 | 0.1107 |
| 0.1109 | 0.54 | 60 | 0.0863 |
| 0.0885 | 0.63 | 70 | 0.0826 |
| 0.081 | 0.73 | 80 | 0.0820 |
| 0.0793 | 0.82 | 90 | 0.0738 |
| 0.0804 | 0.91 | 100 | 0.0770 |
| 0.084 | 1.0 | 110 | 0.0733 |
| 0.078 | 1.09 | 120 | 0.0719 |
| 0.0745 | 1.18 | 130 | 0.0741 |
| 0.0835 | 1.27 | 140 | 0.0727 |
| 0.0738 | 1.36 | 150 | 0.0723 |
| 0.0808 | 1.45 | 160 | 0.0760 |
| 0.0772 | 1.54 | 170 | 0.0687 |
| 0.08 | 1.63 | 180 | 0.0687 |
| 0.0745 | 1.72 | 190 | 0.0663 |
| 0.0742 | 1.81 | 200 | 0.0678 |
| 0.0672 | 1.9 | 210 | 0.0693 |
| 0.0671 | 1.99 | 220 | 0.0643 |
| 0.0571 | 2.08 | 230 | 0.0643 |
| 0.061 | 2.18 | 240 | 0.0639 |
| 0.0611 | 2.27 | 250 | 0.0617 |
| 0.0551 | 2.36 | 260 | 0.0645 |
| 0.0615 | 2.45 | 270 | 0.0599 |
| 0.0552 | 2.54 | 280 | 0.0593 |
| 0.0533 | 2.63 | 290 | 0.0580 |
| 0.0551 | 2.72 | 300 | 0.0573 |
| 0.0592 | 2.81 | 310 | 0.0569 |
| 0.0524 | 2.9 | 320 | 0.0566 |
| 0.0536 | 2.99 | 330 | 0.0564 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- May 4, 2024
- Updated
- May 4, 2024