---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0415MA3plus
  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. -->

# V0415MA3plus

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: 0.0764

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7971        | 0.09  | 10   | 0.1919          |
| 0.1458        | 0.18  | 20   | 0.1068          |
| 0.1006        | 0.27  | 30   | 0.0813          |
| 0.0868        | 0.36  | 40   | 0.0727          |
| 0.0776        | 0.45  | 50   | 0.0726          |
| 0.083         | 0.54  | 60   | 0.0739          |
| 0.0688        | 0.63  | 70   | 0.0666          |
| 0.0645        | 0.73  | 80   | 0.0682          |
| 0.0721        | 0.82  | 90   | 0.0621          |
| 0.0742        | 0.91  | 100  | 0.0638          |
| 0.0683        | 1.0   | 110  | 0.0668          |
| 0.0484        | 1.09  | 120  | 0.0707          |
| 0.0567        | 1.18  | 130  | 0.0647          |
| 0.0553        | 1.27  | 140  | 0.0635          |
| 0.0515        | 1.36  | 150  | 0.0649          |
| 0.0581        | 1.45  | 160  | 0.0615          |
| 0.0486        | 1.54  | 170  | 0.0688          |
| 0.052         | 1.63  | 180  | 0.0634          |
| 0.0482        | 1.72  | 190  | 0.0638          |
| 0.055         | 1.81  | 200  | 0.0606          |
| 0.0469        | 1.9   | 210  | 0.0629          |
| 0.0439        | 1.99  | 220  | 0.0682          |
| 0.0278        | 2.08  | 230  | 0.0611          |
| 0.0241        | 2.18  | 240  | 0.0702          |
| 0.022         | 2.27  | 250  | 0.0783          |
| 0.0203        | 2.36  | 260  | 0.0805          |
| 0.0226        | 2.45  | 270  | 0.0801          |
| 0.0207        | 2.54  | 280  | 0.0819          |
| 0.0198        | 2.63  | 290  | 0.0807          |
| 0.025         | 2.72  | 300  | 0.0785          |
| 0.0286        | 2.81  | 310  | 0.0769          |
| 0.0239        | 2.9   | 320  | 0.0764          |
| 0.025         | 2.99  | 330  | 0.0764          |


### Framework versions

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