---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: phi3.5-mini-adapter_v0
  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. -->

# phi3.5-mini-adapter_v0

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: 0.0423

## 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: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 250

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 11.9711       | 0.1509 | 10   | 10.5546         |
| 0.0847        | 0.3019 | 20   | 0.1104          |
| 0.0989        | 0.4528 | 30   | 0.0840          |
| 0.0543        | 0.6038 | 40   | 0.0588          |
| 0.0392        | 0.7547 | 50   | 0.0490          |
| 0.0447        | 0.9057 | 60   | 0.0457          |
| 0.0465        | 1.0566 | 70   | 0.0435          |
| 0.0317        | 1.2075 | 80   | 0.0445          |
| 0.0443        | 1.3585 | 90   | 0.0423          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1