---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA10
  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. -->

# Phi0503HMA10

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: 0.1439

## 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.5505        | 0.09  | 10   | 1.2821          |
| 0.516         | 0.18  | 20   | 0.2954          |
| 0.2842        | 0.27  | 30   | 0.3173          |
| 0.3169        | 0.36  | 40   | 0.4883          |
| 0.4946        | 0.45  | 50   | 0.2295          |
| 0.6098        | 0.54  | 60   | 1.0244          |
| 0.567         | 0.63  | 70   | 0.2381          |
| 0.2346        | 0.73  | 80   | 0.2265          |
| 0.2844        | 0.82  | 90   | 0.2214          |
| 4.2973        | 0.91  | 100  | 2.3953          |
| 1.7624        | 1.0   | 110  | 1.0186          |
| 0.7104        | 1.09  | 120  | 0.4461          |
| 0.3678        | 1.18  | 130  | 0.2999          |
| 0.2858        | 1.27  | 140  | 0.2034          |
| 0.224         | 1.36  | 150  | 0.1894          |
| 0.2127        | 1.45  | 160  | 0.2045          |
| 0.2229        | 1.54  | 170  | 0.1843          |
| 0.1846        | 1.63  | 180  | 0.1824          |
| 0.1745        | 1.72  | 190  | 0.1665          |
| 0.1676        | 1.81  | 200  | 0.1567          |
| 0.1583        | 1.9   | 210  | 0.1572          |
| 0.1475        | 1.99  | 220  | 0.1532          |
| 0.1529        | 2.08  | 230  | 0.1466          |
| 0.1481        | 2.18  | 240  | 0.1453          |
| 0.1474        | 2.27  | 250  | 0.1497          |
| 0.1479        | 2.36  | 260  | 0.1471          |
| 0.1404        | 2.45  | 270  | 0.1438          |
| 0.1457        | 2.54  | 280  | 0.1444          |
| 0.147         | 2.63  | 290  | 0.1451          |
| 0.1451        | 2.72  | 300  | 0.1444          |
| 0.1508        | 2.81  | 310  | 0.1442          |
| 0.1447        | 2.9   | 320  | 0.1439          |
| 0.1425        | 2.99  | 330  | 0.1439          |


### Framework versions

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