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---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-LoRA
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-3-mini-LoRA
This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3840
## 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: 4
- eval_batch_size: 4
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 120
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.5071 | 0.5882 | 5 | 1.4674 |
| 1.1659 | 1.1765 | 10 | 1.0849 |
| 0.894 | 1.7647 | 15 | 0.8655 |
| 0.7243 | 2.3529 | 20 | 0.6989 |
| 0.5752 | 2.9412 | 25 | 0.5856 |
| 0.5724 | 3.5294 | 30 | 0.5257 |
| 0.4834 | 4.1176 | 35 | 0.4875 |
| 0.3861 | 4.7059 | 40 | 0.4588 |
| 0.35 | 5.2941 | 45 | 0.4368 |
| 0.3126 | 5.8824 | 50 | 0.4251 |
| 0.367 | 6.4706 | 55 | 0.4080 |
| 0.2792 | 7.0588 | 60 | 0.3955 |
| 0.3952 | 7.6471 | 65 | 0.3914 |
| 0.2854 | 8.2353 | 70 | 0.3784 |
| 0.3224 | 8.8235 | 75 | 0.3867 |
| 0.3187 | 9.4118 | 80 | 0.3765 |
| 0.1675 | 10.0 | 85 | 0.3799 |
| 0.1888 | 10.5882 | 90 | 0.3858 |
| 0.2021 | 11.1765 | 95 | 0.3759 |
| 0.1518 | 11.7647 | 100 | 0.3868 |
| 0.2075 | 12.3529 | 105 | 0.3915 |
| 0.1497 | 12.9412 | 110 | 0.3814 |
| 0.1797 | 13.5294 | 115 | 0.3821 |
| 0.1606 | 14.1176 | 120 | 0.3840 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0 |