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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 |