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Phi0511B1
Litzy619/Phi0511B1
Phi0511B1 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 May 12, 2024
Parameters
3.8B
7.7 GB on disk
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.safetensors7.7 GB · 100%
Parameter types
How the weights are stored.
BF163.8B · 100%
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. -->
Phi0511B1
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0690
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: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.1765 | 0.09 | 10 | 4.1064 |
| 2.6213 | 0.18 | 20 | 0.8942 |
| 0.4793 | 0.27 | 30 | 0.1858 |
| 0.1596 | 0.36 | 40 | 0.1426 |
| 0.1372 | 0.45 | 50 | 0.1380 |
| 0.1401 | 0.54 | 60 | 0.1201 |
| 0.1139 | 0.63 | 70 | 0.1011 |
| 0.0995 | 0.73 | 80 | 0.0856 |
| 0.075 | 0.82 | 90 | 0.0778 |
| 0.078 | 0.91 | 100 | 0.0724 |
| 0.0685 | 1.0 | 110 | 0.0689 |
| 0.0577 | 1.09 | 120 | 0.0669 |
| 0.0531 | 1.18 | 130 | 0.0692 |
| 0.0622 | 1.27 | 140 | 0.0650 |
| 0.0561 | 1.36 | 150 | 0.0643 |
| 0.0595 | 1.45 | 160 | 0.0632 |
| 0.0555 | 1.54 | 170 | 0.0630 |
| 0.0549 | 1.63 | 180 | 0.0620 |
| 0.052 | 1.72 | 190 | 0.0627 |
| 0.0577 | 1.81 | 200 | 0.0595 |
| 0.0451 | 1.9 | 210 | 0.0612 |
| 0.0513 | 1.99 | 220 | 0.0626 |
| 0.0377 | 2.08 | 230 | 0.0629 |
| 0.0412 | 2.18 | 240 | 0.0663 |
| 0.0321 | 2.27 | 250 | 0.0701 |
| 0.034 | 2.36 | 260 | 0.0720 |
| 0.0366 | 2.45 | 270 | 0.0718 |
| 0.0323 | 2.54 | 280 | 0.0707 |
| 0.0337 | 2.63 | 290 | 0.0703 |
| 0.0371 | 2.72 | 300 | 0.0699 |
| 0.0417 | 2.81 | 310 | 0.0692 |
| 0.0383 | 2.9 | 320 | 0.0690 |
| 0.0346 | 2.99 | 330 | 0.0690 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- mit
- Created
- May 12, 2024
- Updated
- May 12, 2024