---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0413TUNE
  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. -->

# V0413TUNE

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: 0.0419

## 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: 0.003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6884        | 0.09  | 20   | 0.1584          |
| 0.1153        | 0.18  | 40   | 0.0993          |
| 0.096         | 0.27  | 60   | 0.0854          |
| 0.1014        | 0.36  | 80   | 0.0820          |
| 0.0813        | 0.45  | 100  | 0.0795          |
| 0.0869        | 0.54  | 120  | 0.0707          |
| 0.0858        | 0.63  | 140  | 0.0831          |
| 0.0841        | 0.73  | 160  | 0.0780          |
| 0.0895        | 0.82  | 180  | 0.0732          |
| 0.0908        | 0.91  | 200  | 0.0808          |
| 0.0872        | 1.0   | 220  | 0.0807          |
| 0.0726        | 1.09  | 240  | 0.0720          |
| 0.0644        | 1.18  | 260  | 0.0740          |
| 0.216         | 1.27  | 280  | 0.2003          |
| 0.0945        | 1.36  | 300  | 0.0814          |
| 0.0937        | 1.45  | 320  | 0.0842          |
| 0.0868        | 1.54  | 340  | 0.0801          |
| 0.0714        | 1.63  | 360  | 0.0709          |
| 0.0632        | 1.72  | 380  | 0.0639          |
| 0.0626        | 1.81  | 400  | 0.0518          |
| 0.0467        | 1.9   | 420  | 0.0510          |
| 0.0541        | 1.99  | 440  | 0.0475          |
| 0.0486        | 2.08  | 460  | 0.0580          |
| 0.046         | 2.18  | 480  | 0.0484          |
| 0.0385        | 2.27  | 500  | 0.0493          |
| 0.0446        | 2.36  | 520  | 0.0470          |
| 0.037         | 2.45  | 540  | 0.0424          |
| 0.0446        | 2.54  | 560  | 0.0433          |
| 0.0297        | 2.63  | 580  | 0.0441          |
| 0.0317        | 2.72  | 600  | 0.0426          |
| 0.0481        | 2.81  | 620  | 0.0425          |
| 0.0318        | 2.9   | 640  | 0.0421          |
| 0.0332        | 2.99  | 660  | 0.0419          |


### Framework versions

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