---
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-tool
  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-tool

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: 0.4301

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9379        | 0.2256 | 50   | 0.9483          |
| 0.5752        | 0.4512 | 100  | 0.5681          |
| 0.5014        | 0.6768 | 150  | 0.4917          |
| 0.5155        | 0.9024 | 200  | 0.4731          |
| 0.4501        | 1.1280 | 250  | 0.4633          |
| 0.4451        | 1.3536 | 300  | 0.4565          |
| 0.4214        | 1.5792 | 350  | 0.4517          |
| 0.4795        | 1.8049 | 400  | 0.4477          |
| 0.4448        | 2.0305 | 450  | 0.4447          |
| 0.4181        | 2.2561 | 500  | 0.4423          |
| 0.4353        | 2.4817 | 550  | 0.4403          |
| 0.4613        | 2.7073 | 600  | 0.4386          |
| 0.4573        | 2.9329 | 650  | 0.4371          |
| 0.4719        | 3.1585 | 700  | 0.4362          |
| 0.4174        | 3.3841 | 750  | 0.4347          |
| 0.4337        | 3.6097 | 800  | 0.4340          |
| 0.4478        | 3.8353 | 850  | 0.4332          |
| 0.4156        | 4.0609 | 900  | 0.4325          |
| 0.4177        | 4.2865 | 950  | 0.4318          |
| 0.4113        | 4.5121 | 1000 | 0.4315          |
| 0.4343        | 4.7377 | 1050 | 0.4311          |
| 0.423         | 4.9633 | 1100 | 0.4307          |
| 0.4492        | 5.1889 | 1150 | 0.4307          |
| 0.4417        | 5.4146 | 1200 | 0.4303          |
| 0.4485        | 5.6402 | 1250 | 0.4302          |
| 0.4374        | 5.8658 | 1300 | 0.4301          |


### Framework versions

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