---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0422MADP7B
  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. -->

# V0422MADP7B

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: 0.1474

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.8428        | 0.09  | 10   | 2.3011          |
| 3.8019        | 0.18  | 20   | 1.5011          |
| 1.0644        | 0.27  | 30   | 0.5040          |
| 0.2886        | 0.36  | 40   | 0.2186          |
| 0.1731        | 0.45  | 50   | 0.1452          |
| 0.1635        | 0.54  | 60   | 0.1457          |
| 0.1574        | 0.63  | 70   | 0.1521          |
| 0.1584        | 0.73  | 80   | 0.1515          |
| 0.18          | 0.82  | 90   | 0.1887          |
| 0.167         | 0.91  | 100  | 0.1656          |
| 0.1696        | 1.0   | 110  | 0.1662          |
| 0.1667        | 1.09  | 120  | 0.1703          |
| 0.1858        | 1.18  | 130  | 0.1742          |
| 0.1668        | 1.27  | 140  | 0.1581          |
| 0.1743        | 1.36  | 150  | 0.1651          |
| 0.1582        | 1.45  | 160  | 0.1499          |
| 0.1559        | 1.54  | 170  | 0.1592          |
| 0.1592        | 1.63  | 180  | 0.1520          |
| 0.1574        | 1.72  | 190  | 0.1545          |
| 0.1583        | 1.81  | 200  | 0.1523          |
| 0.1661        | 1.9   | 210  | 0.1628          |
| 0.159         | 1.99  | 220  | 0.1527          |
| 0.1561        | 2.08  | 230  | 0.1493          |
| 0.1479        | 2.18  | 240  | 0.1483          |
| 0.1494        | 2.27  | 250  | 0.1485          |
| 0.1506        | 2.36  | 260  | 0.1482          |
| 0.1486        | 2.45  | 270  | 0.1487          |
| 0.1471        | 2.54  | 280  | 0.1486          |
| 0.148         | 2.63  | 290  | 0.1473          |
| 0.1467        | 2.72  | 300  | 0.1474          |
| 0.1487        | 2.81  | 310  | 0.1474          |
| 0.1501        | 2.9   | 320  | 0.1473          |
| 0.1508        | 2.99  | 330  | 0.1474          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1