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V0413TUNE
Litzy619/V0413TUNE
V0413TUNE 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 15, 2024
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212 GB on disk
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.safetensors5.6 GB · 99%
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F162.8B · 99%
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. -->
V0413TUNE
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: 0.0419
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: 0.003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6884 | 0.09 | 20 | 0.1584 |
| 0.1153 | 0.18 | 40 | 0.0993 |
| 0.096 | 0.27 | 60 | 0.0854 |
| 0.1014 | 0.36 | 80 | 0.0820 |
| 0.0813 | 0.45 | 100 | 0.0795 |
| 0.0869 | 0.54 | 120 | 0.0707 |
| 0.0858 | 0.63 | 140 | 0.0831 |
| 0.0841 | 0.73 | 160 | 0.0780 |
| 0.0895 | 0.82 | 180 | 0.0732 |
| 0.0908 | 0.91 | 200 | 0.0808 |
| 0.0872 | 1.0 | 220 | 0.0807 |
| 0.0726 | 1.09 | 240 | 0.0720 |
| 0.0644 | 1.18 | 260 | 0.0740 |
| 0.216 | 1.27 | 280 | 0.2003 |
| 0.0945 | 1.36 | 300 | 0.0814 |
| 0.0937 | 1.45 | 320 | 0.0842 |
| 0.0868 | 1.54 | 340 | 0.0801 |
| 0.0714 | 1.63 | 360 | 0.0709 |
| 0.0632 | 1.72 | 380 | 0.0639 |
| 0.0626 | 1.81 | 400 | 0.0518 |
| 0.0467 | 1.9 | 420 | 0.0510 |
| 0.0541 | 1.99 | 440 | 0.0475 |
| 0.0486 | 2.08 | 460 | 0.0580 |
| 0.046 | 2.18 | 480 | 0.0484 |
| 0.0385 | 2.27 | 500 | 0.0493 |
| 0.0446 | 2.36 | 520 | 0.0470 |
| 0.037 | 2.45 | 540 | 0.0424 |
| 0.0446 | 2.54 | 560 | 0.0433 |
| 0.0297 | 2.63 | 580 | 0.0441 |
| 0.0317 | 2.72 | 600 | 0.0426 |
| 0.0481 | 2.81 | 620 | 0.0425 |
| 0.0318 | 2.9 | 640 | 0.0421 |
| 0.0332 | 2.99 | 660 | 0.0419 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 14, 2024
- Updated
- Apr 15, 2024