---
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-embedding-step1
  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-embedding-step1

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: 0.5820

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7683        | 0.2256 | 50   | 0.7572          |
| 0.5568        | 0.4512 | 100  | 0.5648          |
| 0.5259        | 0.6768 | 150  | 0.5344          |
| 0.5689        | 0.9024 | 200  | 0.5199          |
| 0.4983        | 1.1280 | 250  | 0.5107          |
| 0.4835        | 1.3536 | 300  | 0.5050          |
| 0.4492        | 1.5792 | 350  | 0.5019          |
| 0.4918        | 1.8049 | 400  | 0.4996          |
| 0.4735        | 2.0305 | 450  | 0.4997          |
| 0.4139        | 2.2561 | 500  | 0.5017          |
| 0.451         | 2.4817 | 550  | 0.5025          |
| 0.4516        | 2.7073 | 600  | 0.5047          |
| 0.4586        | 2.9329 | 650  | 0.5086          |
| 0.4393        | 3.1585 | 700  | 0.5176          |
| 0.4207        | 3.3841 | 750  | 0.5206          |
| 0.3999        | 3.6097 | 800  | 0.5249          |
| 0.414         | 3.8353 | 850  | 0.5327          |
| 0.4002        | 4.0609 | 900  | 0.5408          |
| 0.3651        | 4.2865 | 950  | 0.5498          |
| 0.3775        | 4.5121 | 1000 | 0.5528          |
| 0.4012        | 4.7377 | 1050 | 0.5595          |
| 0.3676        | 4.9633 | 1100 | 0.5668          |
| 0.3634        | 5.1889 | 1150 | 0.5741          |
| 0.3821        | 5.4146 | 1200 | 0.5793          |
| 0.3903        | 5.6402 | 1250 | 0.5815          |
| 0.3655        | 5.8658 | 1300 | 0.5820          |


### Framework versions

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