---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA9
  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. -->

# Phi0503HMA9

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: 0.0673

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.4583        | 0.09  | 10   | 0.9323          |
| 0.4372        | 0.18  | 20   | 0.2609          |
| 0.6807        | 0.27  | 30   | 0.3165          |
| 0.2591        | 0.36  | 40   | 0.2379          |
| 0.2397        | 0.45  | 50   | 0.2319          |
| 0.2086        | 0.54  | 60   | 0.1902          |
| 0.1866        | 0.63  | 70   | 0.1773          |
| 0.1667        | 0.73  | 80   | 0.1585          |
| 0.1097        | 0.82  | 90   | 0.0932          |
| 0.0865        | 0.91  | 100  | 0.0821          |
| 0.0846        | 1.0   | 110  | 0.0800          |
| 0.074         | 1.09  | 120  | 0.0792          |
| 0.0682        | 1.18  | 130  | 0.0861          |
| 0.0765        | 1.27  | 140  | 0.0778          |
| 0.0711        | 1.36  | 150  | 0.0767          |
| 0.08          | 1.45  | 160  | 0.0786          |
| 0.0725        | 1.54  | 170  | 0.0716          |
| 0.07          | 1.63  | 180  | 0.0709          |
| 0.0589        | 1.72  | 190  | 0.1346          |
| 0.4282        | 1.81  | 200  | 0.1490          |
| 0.32          | 1.9   | 210  | 0.1215          |
| 0.2609        | 1.99  | 220  | 0.1303          |
| 0.0654        | 2.08  | 230  | 0.0749          |
| 0.0484        | 2.18  | 240  | 0.0765          |
| 0.0417        | 2.27  | 250  | 0.0716          |
| 0.0437        | 2.36  | 260  | 0.0718          |
| 0.0477        | 2.45  | 270  | 0.0689          |
| 0.0379        | 2.54  | 280  | 0.0696          |
| 0.037         | 2.63  | 290  | 0.0692          |
| 0.0411        | 2.72  | 300  | 0.0689          |
| 0.0457        | 2.81  | 310  | 0.0675          |
| 0.0408        | 2.9   | 320  | 0.0669          |
| 0.0422        | 2.99  | 330  | 0.0673          |


### Framework versions

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