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phi-3-mini-QLoRA
sujithatz/phi-3-mini-QLoRA
phi-3-mini-QLoRA is a machine learning model from sujithatz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- Oct 2, 2024
- Updated
- Oct 17, 2024
- SHA
- bc428ab5
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. -->
phi-3-mini-QLoRA
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: 0.6126
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: 6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- training_steps: 250
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3693 | 0.6667 | 5 | 1.3378 |
| 1.1643 | 1.3333 | 10 | 1.1047 |
| 0.8388 | 2.0 | 15 | 0.8767 |
| 0.6894 | 2.6667 | 20 | 0.6828 |
| 0.5636 | 3.3333 | 25 | 0.5688 |
| 0.4496 | 4.0 | 30 | 0.5110 |
| 0.3487 | 4.6667 | 35 | 0.4549 |
| 0.3169 | 5.3333 | 40 | 0.4148 |
| 0.2595 | 6.0 | 45 | 0.3893 |
| 0.2002 | 6.6667 | 50 | 0.3733 |
| 0.2437 | 7.3333 | 55 | 0.3597 |
| 0.1669 | 8.0 | 60 | 0.3456 |
| 0.1873 | 8.6667 | 65 | 0.3491 |
| 0.1831 | 9.3333 | 70 | 0.3422 |
| 0.1581 | 10.0 | 75 | 0.3664 |
| 0.0831 | 10.6667 | 80 | 0.3644 |
| 0.1277 | 11.3333 | 85 | 0.3822 |
| 0.0539 | 12.0 | 90 | 0.3868 |
| 0.0799 | 12.6667 | 95 | 0.4190 |
| 0.066 | 13.3333 | 100 | 0.4375 |
| 0.0564 | 14.0 | 105 | 0.4581 |
| 0.0356 | 14.6667 | 110 | 0.4715 |
| 0.0493 | 15.3333 | 115 | 0.4896 |
| 0.0399 | 16.0 | 120 | 0.5066 |
| 0.0452 | 16.6667 | 125 | 0.5022 |
| 0.0305 | 17.3333 | 130 | 0.5246 |
| 0.036 | 18.0 | 135 | 0.5492 |
| 0.0282 | 18.6667 | 140 | 0.5537 |
| 0.0327 | 19.3333 | 145 | 0.5703 |
| 0.0341 | 20.0 | 150 | 0.5699 |
| 0.0315 | 20.6667 | 155 | 0.5761 |
| 0.0284 | 21.3333 | 160 | 0.5781 |
| 0.027 | 22.0 | 165 | 0.5818 |
| 0.0258 | 22.6667 | 170 | 0.5858 |
| 0.0224 | 23.3333 | 175 | 0.5884 |
| 0.0253 | 24.0 | 180 | 0.5960 |
| 0.0232 | 24.6667 | 185 | 0.6015 |
| 0.0256 | 25.3333 | 190 | 0.6088 |
| 0.0226 | 26.0 | 195 | 0.6106 |
| 0.0226 | 26.6667 | 200 | 0.6096 |
| 0.0259 | 27.3333 | 205 | 0.6102 |
| 0.0217 | 28.0 | 210 | 0.6100 |
| 0.022 | 28.6667 | 215 | 0.6115 |
| 0.0219 | 29.3333 | 220 | 0.6115 |
| 0.0239 | 30.0 | 225 | 0.6109 |
| 0.0226 | 30.6667 | 230 | 0.6123 |
| 0.0219 | 31.3333 | 235 | 0.6140 |
| 0.0201 | 32.0 | 240 | 0.6128 |
| 0.0198 | 32.6667 | 245 | 0.6130 |
| 0.0234 | 33.3333 | 250 | 0.6126 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
- Library
- peft
- License
- mit
- Created
- Oct 2, 2024
- Updated
- Oct 17, 2024