---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: phi3.5-mini-adapter_v2
  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_v2

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: 0.1344

## 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-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 17.6422       | 0.4545 | 10   | 17.2166         |
| 13.0308       | 0.9091 | 20   | 12.5267         |
| 8.4662        | 1.3636 | 30   | 7.9483          |
| 2.4521        | 1.8182 | 40   | 1.3982          |
| 0.3917        | 2.2727 | 50   | 0.3427          |
| 0.3042        | 2.7273 | 60   | 0.3092          |
| 0.2051        | 3.1818 | 70   | 0.2451          |
| 0.2043        | 3.6364 | 80   | 0.2022          |
| 0.1599        | 4.0909 | 90   | 0.1907          |
| 0.1658        | 4.5455 | 100  | 0.1727          |
| 0.1527        | 5.0    | 110  | 0.1595          |
| 0.1281        | 5.4545 | 120  | 0.1501          |
| 0.1079        | 5.9091 | 130  | 0.1435          |
| 0.0896        | 6.3636 | 140  | 0.1369          |
| 0.097         | 6.8182 | 150  | 0.1340          |
| 0.0841        | 7.2727 | 160  | 0.1449          |
| 0.0771        | 7.7273 | 170  | 0.1344          |


### Framework versions

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