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---
library_name: peft
license: mit
base_model: microsoft/Phi-4-mini-instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Phi-4-mini-instruct_sft_sg_values_resp_split
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. -->
# Phi-4-mini-instruct_sft_sg_values_resp_split
This model is a fine-tuned version of [microsoft/Phi-4-mini-instruct](https://huggingface.co/microsoft/Phi-4-mini-instruct) on the sft_sg_values_res_split dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3214
## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.3698 | 0.1710 | 250 | 4.1731 |
| 3.5096 | 0.3419 | 500 | 3.1497 |
| 2.6213 | 0.5129 | 750 | 2.5736 |
| 2.4305 | 0.6839 | 1000 | 2.3980 |
| 2.3653 | 0.8548 | 1250 | 2.3345 |
### Framework versions
- PEFT 0.15.2
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.1 |