| | --- |
| | library_name: peft |
| | license: mit |
| | base_model: microsoft/Phi-4-mini-instruct |
| | tags: |
| | - base_model:adapter:microsoft/Phi-4-mini-instruct |
| | - lora |
| | - transformers |
| | model-index: |
| | - name: phi4_instruct_20250902_0749 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # phi4_instruct_20250902_0749 |
| | |
| | This model is a fine-tuned version of [microsoft/Phi-4-mini-instruct](https://huggingface.co/microsoft/Phi-4-mini-instruct) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6032 |
| | - Map@3: 0.8772 |
| | |
| | ## 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: 0.0002 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 64 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 | Map@3 | |
| | |:-------------:|:------:|:----:|:---------------:|:------:| |
| | | 16.4003 | 0.0523 | 20 | 1.3662 | 0.7260 | |
| | | 9.5268 | 0.1046 | 40 | 1.0851 | 0.7793 | |
| | | 8.3438 | 0.1569 | 60 | 0.9705 | 0.7830 | |
| | | 7.495 | 0.2092 | 80 | 0.9053 | 0.8070 | |
| | | 7.4283 | 0.2615 | 100 | 0.8488 | 0.8326 | |
| | | 6.5147 | 0.3138 | 120 | 0.7270 | 0.8505 | |
| | | 5.6739 | 0.3661 | 140 | 0.7694 | 0.8445 | |
| | | 5.8069 | 0.4184 | 160 | 0.6465 | 0.8692 | |
| | | 5.8288 | 0.4707 | 180 | 0.6613 | 0.8537 | |
| | | 4.7902 | 0.5230 | 200 | 0.6032 | 0.8827 | |
| | | 5.0708 | 0.5754 | 220 | 0.5588 | 0.8832 | |
| | | 4.7105 | 0.6277 | 240 | 0.5590 | 0.8880 | |
| | | 4.6516 | 0.6800 | 260 | 0.5281 | 0.8944 | |
| | | 4.2103 | 0.7323 | 280 | 0.5666 | 0.8824 | |
| | | 4.9022 | 0.7846 | 300 | 0.5486 | 0.8936 | |
| | | 3.8328 | 0.8369 | 320 | 0.5402 | 0.8959 | |
| | | 4.2973 | 0.8892 | 340 | 0.5149 | 0.9046 | |
| | | 3.8971 | 0.9415 | 360 | 0.4942 | 0.8943 | |
| | | 3.9711 | 0.9938 | 380 | 0.5736 | 0.8894 | |
| | | 3.6985 | 1.0445 | 400 | 0.5119 | 0.9000 | |
| | | 2.971 | 1.0968 | 420 | 0.6032 | 0.8772 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.17.1 |
| | - Transformers 4.56.0 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.0 |
