---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0417MADP2
  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. -->

# V0417MADP2

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1574

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.5044        | 0.09  | 10   | 3.0469          |
| 7.1174        | 0.18  | 20   | 2.9171          |
| 6.0751        | 0.27  | 30   | 2.6390          |
| 4.2708        | 0.36  | 40   | 2.0163          |
| 2.4666        | 0.45  | 50   | 1.5118          |
| 1.3427        | 0.54  | 60   | 0.8933          |
| 0.5622        | 0.63  | 70   | 0.4358          |
| 0.2583        | 0.73  | 80   | 0.2698          |
| 0.2135        | 0.82  | 90   | 0.2154          |
| 0.1981        | 0.91  | 100  | 0.1957          |
| 0.1955        | 1.0   | 110  | 0.1945          |
| 0.2021        | 1.09  | 120  | 0.2029          |
| 0.1932        | 1.18  | 130  | 0.1893          |
| 0.1726        | 1.27  | 140  | 0.1965          |
| 0.1813        | 1.36  | 150  | 0.1825          |
| 0.1865        | 1.45  | 160  | 0.1699          |
| 0.1787        | 1.54  | 170  | 0.1609          |
| 0.1634        | 1.63  | 180  | 0.1666          |
| 0.1673        | 1.72  | 190  | 0.1703          |
| 0.2204        | 1.81  | 200  | 0.1684          |
| 0.1751        | 1.9   | 210  | 0.1619          |
| 0.1656        | 1.99  | 220  | 0.1665          |
| 0.1717        | 2.08  | 230  | 0.1583          |
| 0.1664        | 2.18  | 240  | 0.1635          |
| 0.1682        | 2.27  | 250  | 0.1628          |
| 0.1729        | 2.36  | 260  | 0.1635          |
| 0.1703        | 2.45  | 270  | 0.1622          |
| 0.168         | 2.54  | 280  | 0.1578          |
| 0.1588        | 2.63  | 290  | 0.1564          |
| 0.1554        | 2.72  | 300  | 0.1571          |
| 0.1566        | 2.81  | 310  | 0.1573          |
| 0.1602        | 2.9   | 320  | 0.1572          |
| 0.1587        | 2.99  | 330  | 0.1574          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1