---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0503HMA5H
  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. -->

# V0503HMA5H

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: 0.1346

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7787        | 0.09  | 10   | 0.1611          |
| 0.1597        | 0.18  | 20   | 0.1230          |
| 0.1177        | 0.27  | 30   | 0.1023          |
| 0.1021        | 0.36  | 40   | 0.0896          |
| 0.085         | 0.45  | 50   | 0.0808          |
| 0.0884        | 0.54  | 60   | 0.0808          |
| 0.0855        | 0.63  | 70   | 0.0706          |
| 0.0789        | 0.73  | 80   | 0.0902          |
| 0.087         | 0.82  | 90   | 0.0869          |
| 0.1125        | 0.91  | 100  | 8.7126          |
| 2.2018        | 1.0   | 110  | 0.4319          |
| 0.2705        | 1.09  | 120  | 0.2003          |
| 0.759         | 1.18  | 130  | 0.2586          |
| 0.2778        | 1.27  | 140  | 0.1786          |
| 0.191         | 1.36  | 150  | 0.2223          |
| 0.177         | 1.45  | 160  | 0.1639          |
| 0.1691        | 1.54  | 170  | 0.1591          |
| 0.16          | 1.63  | 180  | 0.1638          |
| 0.1535        | 1.72  | 190  | 0.1508          |
| 0.1501        | 1.81  | 200  | 0.1572          |
| 0.1549        | 1.9   | 210  | 0.1487          |
| 0.1523        | 1.99  | 220  | 0.1505          |
| 0.1538        | 2.08  | 230  | 0.1558          |
| 0.1493        | 2.18  | 240  | 0.1474          |
| 0.1438        | 2.27  | 250  | 0.1439          |
| 0.1455        | 2.36  | 260  | 0.1425          |
| 0.1406        | 2.45  | 270  | 0.1433          |
| 0.1402        | 2.54  | 280  | 0.1382          |
| 0.1371        | 2.63  | 290  | 0.1385          |
| 0.138         | 2.72  | 300  | 0.1355          |
| 0.1352        | 2.81  | 310  | 0.1354          |
| 0.1366        | 2.9   | 320  | 0.1347          |
| 0.1368        | 2.99  | 330  | 0.1346          |


### Framework versions

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