---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: Phi0503HMA17
  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. -->

# Phi0503HMA17

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: 0.1875

## 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.75          | 0.09  | 10   | 0.5453          |
| 0.3378        | 0.18  | 20   | 0.2824          |
| 0.3447        | 0.27  | 30   | 0.3174          |
| 0.2287        | 0.36  | 40   | 0.1820          |
| 0.1614        | 0.45  | 50   | 0.1595          |
| 0.1573        | 0.54  | 60   | 0.1415          |
| 0.1433        | 0.63  | 70   | 0.1354          |
| 0.2011        | 0.73  | 80   | 1.2273          |
| 0.311         | 0.82  | 90   | 0.1241          |
| 0.1326        | 0.91  | 100  | 0.1242          |
| 0.129         | 1.0   | 110  | 0.1278          |
| 0.0812        | 1.09  | 120  | 0.0927          |
| 0.1272        | 1.18  | 130  | 0.2229          |
| 3.2223        | 1.27  | 140  | 2.3282          |
| 1.9049        | 1.36  | 150  | 1.0767          |
| 0.8589        | 1.45  | 160  | 0.6321          |
| 0.5045        | 1.54  | 170  | 0.4553          |
| 0.5118        | 1.63  | 180  | 0.3732          |
| 0.3558        | 1.72  | 190  | 0.3349          |
| 0.3136        | 1.81  | 200  | 0.3106          |
| 0.3007        | 1.9   | 210  | 0.2946          |
| 0.3073        | 1.99  | 220  | 0.2602          |
| 0.3275        | 2.08  | 230  | 0.4014          |
| 0.5342        | 2.18  | 240  | 0.4574          |
| 0.3191        | 2.27  | 250  | 0.3423          |
| 0.2647        | 2.36  | 260  | 0.2386          |
| 0.23          | 2.45  | 270  | 0.2366          |
| 0.2493        | 2.54  | 280  | 0.2132          |
| 0.2129        | 2.63  | 290  | 0.2020          |
| 0.2034        | 2.72  | 300  | 0.1892          |
| 0.225         | 2.81  | 310  | 0.1930          |
| 0.1989        | 2.9   | 320  | 0.1899          |
| 0.1969        | 2.99  | 330  | 0.1875          |


### Framework versions

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