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phi-3-law-br
jersobh/phi-3-law-br
phi-3-law-br is a machine learning model from jersobh. 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
- Feb 21, 2025
- Updated
- Feb 21, 2025
- SHA
- 108b91d3
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-law-br
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9687
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 1 | 1.9751 |
| No log | 2.0 | 2 | 1.9708 |
| No log | 3.0 | 3 | 1.9687 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.7.0.dev20250220+cpu
- Datasets 3.2.0
- Tokenizers 0.21.0
- Library
- peft
- License
- mit
- Created
- Feb 21, 2025
- Updated
- Feb 21, 2025