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phi-3-mini-LoRA
rahulavaghan/phi-3-mini-LoRA
phi-3-mini-LoRA is a machine learning model from rahulavaghan. 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
- Aug 29, 2024
- Updated
- Aug 29, 2024
- SHA
- e8b0df1a
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-LoRA
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: 0.8384
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4537 | 0.2052 | 100 | 1.2281 |
| 1.0408 | 0.4105 | 200 | 0.9405 |
| 0.915 | 0.6157 | 300 | 0.9088 |
| 0.9159 | 0.8209 | 400 | 0.8933 |
| 0.8925 | 1.0262 | 500 | 0.8809 |
| 0.8837 | 1.2314 | 600 | 0.8712 |
| 0.8753 | 1.4366 | 700 | 0.8604 |
| 0.8701 | 1.6419 | 800 | 0.8537 |
| 0.8755 | 1.8471 | 900 | 0.8498 |
| 0.8603 | 2.0523 | 1000 | 0.8460 |
| 0.8669 | 2.2576 | 1100 | 0.8434 |
| 0.8558 | 2.4628 | 1200 | 0.8410 |
| 0.8482 | 2.6680 | 1300 | 0.8395 |
| 0.844 | 2.8733 | 1400 | 0.8384 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Library
- peft
- License
- mit
- Created
- Aug 29, 2024
- Updated
- Aug 29, 2024