---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: phi3.5-mini-adapter_v1
  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_v1

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: 0.0998

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 50

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 14.2062       | 0.6061 | 10   | 13.2015         |
| 5.0286        | 1.2121 | 20   | 3.9207          |
| 0.248         | 1.8182 | 30   | 0.2396          |
| 0.1801        | 2.4242 | 40   | 0.1860          |
| 0.1496        | 3.0303 | 50   | 0.1639          |
| 0.212         | 3.6364 | 60   | 0.1333          |
| 0.0822        | 4.2424 | 70   | 0.1134          |
| 0.07          | 4.8485 | 80   | 0.1061          |
| 0.0871        | 5.4545 | 90   | 0.1178          |
| 0.0645        | 6.0606 | 100  | 0.1017          |
| 0.0558        | 6.6667 | 110  | 0.0998          |


### Framework versions

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