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phi-3-mini-LoRA
rahul4862/phi-3-mini-LoRA
phi-3-mini-LoRA is a machine learning model from rahul4862. 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 4, 2024
- Updated
- Aug 5, 2024
- SHA
- 1948063a
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: 1.7121
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 |
|---|---|---|---|
| 1.94 | 0.0953 | 100 | 1.8918 |
| 1.8113 | 0.1907 | 200 | 1.7877 |
| 1.7578 | 0.2860 | 300 | 1.7701 |
| 1.756 | 0.3813 | 400 | 1.7637 |
| 1.7632 | 0.4766 | 500 | 1.7582 |
| 1.7477 | 0.5720 | 600 | 1.7542 |
| 1.7605 | 0.6673 | 700 | 1.7508 |
| 1.7312 | 0.7626 | 800 | 1.7482 |
| 1.7315 | 0.8580 | 900 | 1.7439 |
| 1.7148 | 0.9533 | 1000 | 1.7414 |
| 1.7263 | 1.0486 | 1100 | 1.7385 |
| 1.7184 | 1.1439 | 1200 | 1.7361 |
| 1.7187 | 1.2393 | 1300 | 1.7336 |
| 1.7231 | 1.3346 | 1400 | 1.7313 |
| 1.7433 | 1.4299 | 1500 | 1.7290 |
| 1.6962 | 1.5253 | 1600 | 1.7268 |
| 1.7136 | 1.6206 | 1700 | 1.7253 |
| 1.6969 | 1.7159 | 1800 | 1.7236 |
| 1.7028 | 1.8112 | 1900 | 1.7217 |
| 1.7066 | 1.9066 | 2000 | 1.7200 |
| 1.7123 | 2.0019 | 2100 | 1.7191 |
| 1.7005 | 2.0972 | 2200 | 1.7178 |
| 1.7052 | 2.1926 | 2300 | 1.7168 |
| 1.6946 | 2.2879 | 2400 | 1.7160 |
| 1.6728 | 2.3832 | 2500 | 1.7150 |
| 1.7033 | 2.4786 | 2600 | 1.7144 |
| 1.6893 | 2.5739 | 2700 | 1.7136 |
| 1.7206 | 2.6692 | 2800 | 1.7129 |
| 1.6747 | 2.7645 | 2900 | 1.7126 |
| 1.6981 | 2.8599 | 3000 | 1.7123 |
| 1.6928 | 2.9552 | 3100 | 1.7121 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- mit
- Created
- Aug 4, 2024
- Updated
- Aug 5, 2024