---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0316MP2
  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. -->

# V0316MP2

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: 0.0962

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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: 20
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5399        | 0.09  | 10   | 2.3219          |
| 2.1738        | 0.17  | 20   | 1.8070          |
| 1.6126        | 0.26  | 30   | 1.2246          |
| 1.1047        | 0.34  | 40   | 0.7910          |
| 0.6789        | 0.43  | 50   | 0.3123          |
| 0.3195        | 0.51  | 60   | 0.1536          |
| 0.2157        | 0.6   | 70   | 0.1208          |
| 0.1791        | 0.68  | 80   | 0.1139          |
| 0.16          | 0.77  | 90   | 0.1100          |
| 0.1628        | 0.85  | 100  | 0.1076          |
| 0.1556        | 0.94  | 110  | 0.1066          |
| 0.1509        | 1.02  | 120  | 0.1057          |
| 0.1575        | 1.11  | 130  | 0.1040          |
| 0.1502        | 1.19  | 140  | 0.1038          |
| 0.148         | 1.28  | 150  | 0.1024          |
| 0.1478        | 1.37  | 160  | 0.1019          |
| 0.1469        | 1.45  | 170  | 0.1015          |
| 0.1339        | 1.54  | 180  | 0.1008          |
| 0.1433        | 1.62  | 190  | 0.1002          |
| 0.1408        | 1.71  | 200  | 0.0993          |
| 0.1391        | 1.79  | 210  | 0.0987          |
| 0.1411        | 1.88  | 220  | 0.0980          |
| 0.1345        | 1.96  | 230  | 0.0975          |
| 0.1422        | 2.05  | 240  | 0.0968          |
| 0.1374        | 2.13  | 250  | 0.0970          |
| 0.1341        | 2.22  | 260  | 0.0970          |
| 0.1346        | 2.3   | 270  | 0.0968          |
| 0.1412        | 2.39  | 280  | 0.0966          |
| 0.1339        | 2.47  | 290  | 0.0959          |
| 0.1395        | 2.56  | 300  | 0.0961          |
| 0.1376        | 2.65  | 310  | 0.0961          |
| 0.1384        | 2.73  | 320  | 0.0960          |
| 0.1374        | 2.82  | 330  | 0.0958          |
| 0.1295        | 2.9   | 340  | 0.0959          |
| 0.1298        | 2.99  | 350  | 0.0962          |


### Framework versions

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