---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424MADP5
  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. -->

# V0424MADP5

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: 0.1480

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.3847        | 0.09  | 10   | 2.9270          |
| 4.8632        | 0.18  | 20   | 2.1131          |
| 1.8758        | 0.27  | 30   | 0.8698          |
| 0.3611        | 0.36  | 40   | 0.3136          |
| 0.173         | 0.45  | 50   | 0.1911          |
| 0.1662        | 0.54  | 60   | 0.1774          |
| 0.1615        | 0.63  | 70   | 0.1630          |
| 0.1598        | 0.73  | 80   | 0.1656          |
| 0.1612        | 0.82  | 90   | 0.1598          |
| 0.1547        | 0.91  | 100  | 0.1515          |
| 0.1574        | 1.0   | 110  | 0.1517          |
| 0.1576        | 1.09  | 120  | 0.1557          |
| 0.1616        | 1.18  | 130  | 0.1728          |
| 0.1587        | 1.27  | 140  | 0.1538          |
| 0.156         | 1.36  | 150  | 0.1534          |
| 0.1545        | 1.45  | 160  | 0.1487          |
| 0.1552        | 1.54  | 170  | 0.1612          |
| 0.1578        | 1.63  | 180  | 0.1528          |
| 0.1587        | 1.72  | 190  | 0.1691          |
| 0.1567        | 1.81  | 200  | 0.1491          |
| 0.1619        | 1.9   | 210  | 0.1497          |
| 0.1546        | 1.99  | 220  | 0.1508          |
| 0.1564        | 2.08  | 230  | 0.1497          |
| 0.1481        | 2.18  | 240  | 0.1481          |
| 0.1491        | 2.27  | 250  | 0.1512          |
| 0.1511        | 2.36  | 260  | 0.1504          |
| 0.1519        | 2.45  | 270  | 0.1494          |
| 0.1464        | 2.54  | 280  | 0.1493          |
| 0.148         | 2.63  | 290  | 0.1488          |
| 0.1499        | 2.72  | 300  | 0.1487          |
| 0.1487        | 2.81  | 310  | 0.1480          |
| 0.1484        | 2.9   | 320  | 0.1479          |
| 0.15          | 2.99  | 330  | 0.1480          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1