---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Phi-3.5-MultiCap-6
  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-3.5-MultiCap-6

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: 0.5045

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9384        | 0.2256 | 50   | 0.9431          |
| 0.6189        | 0.4512 | 100  | 0.6235          |
| 0.5667        | 0.6768 | 150  | 0.5738          |
| 0.6109        | 0.9024 | 200  | 0.5533          |
| 0.537         | 1.1280 | 250  | 0.5418          |
| 0.5254        | 1.3536 | 300  | 0.5341          |
| 0.495         | 1.5792 | 350  | 0.5288          |
| 0.5414        | 1.8049 | 400  | 0.5243          |
| 0.5285        | 2.0305 | 450  | 0.5212          |
| 0.4729        | 2.2561 | 500  | 0.5180          |
| 0.5167        | 2.4817 | 550  | 0.5161          |
| 0.5228        | 2.7073 | 600  | 0.5141          |
| 0.5321        | 2.9329 | 650  | 0.5124          |
| 0.5212        | 3.1585 | 700  | 0.5112          |
| 0.5052        | 3.3841 | 750  | 0.5097          |
| 0.4826        | 3.6097 | 800  | 0.5088          |
| 0.5118        | 3.8353 | 850  | 0.5079          |
| 0.4957        | 4.0609 | 900  | 0.5071          |
| 0.4779        | 4.2865 | 950  | 0.5065          |
| 0.4888        | 4.5121 | 1000 | 0.5061          |
| 0.52          | 4.7377 | 1050 | 0.5055          |
| 0.4892        | 4.9633 | 1100 | 0.5052          |
| 0.4881        | 5.1889 | 1150 | 0.5051          |
| 0.5071        | 5.4146 | 1200 | 0.5047          |
| 0.515         | 5.6402 | 1250 | 0.5046          |
| 0.491         | 5.8658 | 1300 | 0.5045          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1