Downloads · 30 days
4
7% of all-time downloads
phi3-mini-LoRA
alexrodpas/phi3-mini-LoRA
phi3-mini-LoRA is a machine learning model from alexrodpas. 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. --
All-time downloads
54
Public
Repo size
35.7 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors35.7 MB · 91%
At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- Oct 3, 2024
- Updated
- Oct 3, 2024
- SHA
- a6f54045
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. -->
phi3-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: 0.5538
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 |
|---|---|---|---|
| 0.8693 | 0.1809 | 100 | 0.6163 |
| 0.5925 | 0.3618 | 200 | 0.5740 |
| 0.5675 | 0.5427 | 300 | 0.5667 |
| 0.571 | 0.7237 | 400 | 0.5631 |
| 0.555 | 0.9046 | 500 | 0.5613 |
| 0.566 | 1.0855 | 600 | 0.5597 |
| 0.5502 | 1.2664 | 700 | 0.5583 |
| 0.5524 | 1.4473 | 800 | 0.5575 |
| 0.5653 | 1.6282 | 900 | 0.5565 |
| 0.5515 | 1.8091 | 1000 | 0.5561 |
| 0.5523 | 1.9900 | 1100 | 0.5555 |
| 0.5422 | 2.1710 | 1200 | 0.5555 |
| 0.559 | 2.3519 | 1300 | 0.5546 |
| 0.5466 | 2.5328 | 1400 | 0.5542 |
| 0.5476 | 2.7137 | 1500 | 0.5541 |
| 0.55 | 2.8946 | 1600 | 0.5538 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.2.2
- Datasets 3.0.1
- Tokenizers 0.20.0
- Library
- peft
- License
- mit
- Created
- Oct 3, 2024
- Updated
- Oct 3, 2024