---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: guru1984
  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. -->

# guru1984

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: 1.9331

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.0802        | 0.0786 | 50   | 3.3923          |
| 2.6833        | 0.1572 | 100  | 2.3272          |
| 2.1534        | 0.2358 | 150  | 2.1625          |
| 2.0476        | 0.3145 | 200  | 2.1005          |
| 1.9929        | 0.3931 | 250  | 2.0717          |
| 1.974         | 0.4717 | 300  | 2.0509          |
| 1.9854        | 0.5503 | 350  | 2.0435          |
| 2.0109        | 0.6289 | 400  | 2.0358          |
| 1.9939        | 0.7075 | 450  | 2.0285          |
| 1.9672        | 0.7862 | 500  | 2.0150          |
| 1.9565        | 0.8648 | 550  | 2.0115          |
| 1.9706        | 0.9434 | 600  | 2.0062          |
| 1.9352        | 1.0220 | 650  | 1.9949          |
| 1.8647        | 1.1006 | 700  | 1.9930          |
| 1.9109        | 1.1792 | 750  | 1.9840          |
| 1.885         | 1.2579 | 800  | 1.9806          |
| 1.8864        | 1.3365 | 850  | 1.9878          |
| 1.8931        | 1.4151 | 900  | 1.9825          |
| 1.8599        | 1.4937 | 950  | 1.9755          |
| 1.9019        | 1.5723 | 1000 | 1.9695          |
| 1.9081        | 1.6509 | 1050 | 1.9599          |
| 1.8736        | 1.7296 | 1100 | 1.9583          |
| 1.8939        | 1.8082 | 1150 | 1.9567          |
| 1.8867        | 1.8868 | 1200 | 1.9534          |
| 1.8875        | 1.9654 | 1250 | 1.9479          |
| 1.8677        | 2.0440 | 1300 | 1.9498          |
| 1.8152        | 2.1226 | 1350 | 1.9527          |
| 1.8573        | 2.2013 | 1400 | 1.9523          |
| 1.8433        | 2.2799 | 1450 | 1.9441          |
| 1.828         | 2.3585 | 1500 | 1.9455          |
| 1.8298        | 2.4371 | 1550 | 1.9423          |
| 1.8258        | 2.5157 | 1600 | 1.9376          |
| 1.8314        | 2.5943 | 1650 | 1.9373          |
| 1.8436        | 2.6730 | 1700 | 1.9394          |
| 1.8253        | 2.7516 | 1750 | 1.9373          |
| 1.8055        | 2.8302 | 1800 | 1.9365          |
| 1.8207        | 2.9088 | 1850 | 1.9342          |
| 1.8514        | 2.9874 | 1900 | 1.9331          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1