---
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-lora
  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-lora

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: 0.4902

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7255        | 0.2256 | 50   | 0.7138          |
| 0.4783        | 0.4512 | 100  | 0.4788          |
| 0.4616        | 0.6768 | 150  | 0.4543          |
| 0.4794        | 0.9024 | 200  | 0.4437          |
| 0.4174        | 1.1280 | 250  | 0.4357          |
| 0.4097        | 1.3536 | 300  | 0.4310          |
| 0.3829        | 1.5792 | 350  | 0.4280          |
| 0.4358        | 1.8049 | 400  | 0.4264          |
| 0.4013        | 2.0305 | 450  | 0.4261          |
| 0.3685        | 2.2561 | 500  | 0.4268          |
| 0.3823        | 2.4817 | 550  | 0.4276          |
| 0.401         | 2.7073 | 600  | 0.4294          |
| 0.3975        | 2.9329 | 650  | 0.4310          |
| 0.4012        | 3.1585 | 700  | 0.4373          |
| 0.3497        | 3.3841 | 750  | 0.4401          |
| 0.3613        | 3.6097 | 800  | 0.4456          |
| 0.3649        | 3.8353 | 850  | 0.4522          |
| 0.3384        | 4.0609 | 900  | 0.4575          |
| 0.3241        | 4.2865 | 950  | 0.4628          |
| 0.322         | 4.5121 | 1000 | 0.4662          |
| 0.3397        | 4.7377 | 1050 | 0.4720          |
| 0.3228        | 4.9633 | 1100 | 0.4788          |
| 0.3391        | 5.1889 | 1150 | 0.4820          |
| 0.3369        | 5.4146 | 1200 | 0.4861          |
| 0.3424        | 5.6402 | 1250 | 0.4873          |
| 0.3302        | 5.8658 | 1300 | 0.4902          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 3.0.0
- Tokenizers 0.19.1