---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA22
  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. -->

# Phi0503HMA22

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0803

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 80
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.2194        | 0.09  | 10   | 0.6300          |
| 0.3395        | 0.18  | 20   | 0.2247          |
| 0.2461        | 0.27  | 30   | 0.2248          |
| 0.2061        | 0.36  | 40   | 0.1918          |
| 0.2198        | 0.45  | 50   | 0.1831          |
| 0.1993        | 0.54  | 60   | 0.1771          |
| 0.1676        | 0.63  | 70   | 0.2615          |
| 0.1316        | 0.73  | 80   | 0.0854          |
| 0.0974        | 0.82  | 90   | 0.0932          |
| 0.0916        | 0.91  | 100  | 0.0787          |
| 0.0794        | 1.0   | 110  | 0.0806          |
| 0.0658        | 1.09  | 120  | 0.0709          |
| 0.0619        | 1.18  | 130  | 0.0891          |
| 0.0724        | 1.27  | 140  | 0.0779          |
| 0.0667        | 1.36  | 150  | 0.0794          |
| 0.0752        | 1.45  | 160  | 0.0705          |
| 0.067         | 1.54  | 170  | 0.0698          |
| 0.0627        | 1.63  | 180  | 0.0712          |
| 0.0604        | 1.72  | 190  | 0.0663          |
| 0.0635        | 1.81  | 200  | 0.0655          |
| 0.0567        | 1.9   | 210  | 0.0668          |
| 0.0553        | 1.99  | 220  | 0.0694          |
| 0.0276        | 2.08  | 230  | 0.0814          |
| 0.0285        | 2.18  | 240  | 0.0992          |
| 0.0254        | 2.27  | 250  | 0.0970          |
| 0.0213        | 2.36  | 260  | 0.0887          |
| 0.0274        | 2.45  | 270  | 0.0850          |
| 0.0203        | 2.54  | 280  | 0.0866          |
| 0.0185        | 2.63  | 290  | 0.0885          |
| 0.0295        | 2.72  | 300  | 0.0845          |
| 0.0314        | 2.81  | 310  | 0.0816          |
| 0.0253        | 2.9   | 320  | 0.0805          |
| 0.0245        | 2.99  | 330  | 0.0803          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0