---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0417MADP3
  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. -->

# V0417MADP3

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: 0.1901

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.5507        | 0.09  | 10   | 3.0786          |
| 6.3727        | 0.18  | 20   | 2.6464          |
| 3.4656        | 0.27  | 30   | 1.9120          |
| 1.5044        | 0.36  | 40   | 1.1144          |
| 0.581         | 0.45  | 50   | 0.7389          |
| 0.3434        | 0.54  | 60   | 0.5960          |
| 0.3386        | 0.63  | 70   | 0.5215          |
| 0.2957        | 0.73  | 80   | 0.5323          |
| 0.258         | 0.82  | 90   | 0.4773          |
| 0.263         | 0.91  | 100  | 0.4986          |
| 0.2584        | 1.0   | 110  | 0.4831          |
| 0.2808        | 1.09  | 120  | 0.5051          |
| 0.2978        | 1.18  | 130  | 0.4790          |
| 0.2479        | 1.27  | 140  | 0.4456          |
| 0.4023        | 1.36  | 150  | 0.4223          |
| 0.21          | 1.45  | 160  | 0.2159          |
| 0.1788        | 1.54  | 170  | 0.2052          |
| 0.1786        | 1.63  | 180  | 0.2024          |
| 0.1748        | 1.72  | 190  | 0.2013          |
| 0.1718        | 1.81  | 200  | 0.2138          |
| 0.176         | 1.9   | 210  | 0.2197          |
| 0.173         | 1.99  | 220  | 0.2321          |
| 0.1877        | 2.08  | 230  | 0.2317          |
| 0.1732        | 2.18  | 240  | 0.2126          |
| 0.1661        | 2.27  | 250  | 0.1958          |
| 0.1668        | 2.36  | 260  | 0.1955          |
| 0.1642        | 2.45  | 270  | 0.1957          |
| 0.1612        | 2.54  | 280  | 0.1937          |
| 0.1681        | 2.63  | 290  | 0.1910          |
| 0.1622        | 2.72  | 300  | 0.1901          |
| 0.1592        | 2.81  | 310  | 0.1898          |
| 0.1657        | 2.9   | 320  | 0.1904          |
| 0.1696        | 2.99  | 330  | 0.1901          |


### Framework versions

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