---
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-mt
  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-mt

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: 0.7569

## 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4288        | 0.1533 | 15   | 1.3449          |
| 1.0894        | 0.3065 | 30   | 1.1240          |
| 0.9541        | 0.4598 | 45   | 0.9830          |
| 0.9216        | 0.6130 | 60   | 0.8949          |
| 0.8675        | 0.7663 | 75   | 0.8414          |
| 0.8007        | 0.9195 | 90   | 0.8108          |
| 0.8205        | 1.0728 | 105  | 0.7919          |
| 0.7864        | 1.2261 | 120  | 0.7794          |
| 0.7983        | 1.3793 | 135  | 0.7705          |
| 0.7784        | 1.5326 | 150  | 0.7641          |
| 0.744         | 1.6858 | 165  | 0.7595          |
| 0.7765        | 1.8391 | 180  | 0.7569          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1