---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0415MA1
  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. -->

# V0415MA1

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: 0.0598

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2693        | 0.09  | 10   | 1.1034          |
| 0.5007        | 0.18  | 20   | 0.1183          |
| 0.1243        | 0.27  | 30   | 0.1078          |
| 0.1244        | 0.36  | 40   | 0.0970          |
| 0.0995        | 0.45  | 50   | 0.0818          |
| 0.0931        | 0.54  | 60   | 0.0755          |
| 0.0789        | 0.63  | 70   | 0.0721          |
| 0.0772        | 0.73  | 80   | 0.0731          |
| 0.0799        | 0.82  | 90   | 0.0635          |
| 0.0756        | 0.91  | 100  | 0.0640          |
| 0.072         | 1.0   | 110  | 0.0657          |
| 0.064         | 1.09  | 120  | 0.0627          |
| 0.0616        | 1.18  | 130  | 0.0610          |
| 0.0587        | 1.27  | 140  | 0.0618          |
| 0.0569        | 1.36  | 150  | 0.0604          |
| 0.0652        | 1.45  | 160  | 0.0624          |
| 0.0617        | 1.54  | 170  | 0.0605          |
| 0.0633        | 1.63  | 180  | 0.0578          |
| 0.0607        | 1.72  | 190  | 0.0573          |
| 0.0673        | 1.81  | 200  | 0.0626          |
| 0.0553        | 1.9   | 210  | 0.0661          |
| 0.055         | 1.99  | 220  | 0.0647          |
| 0.0433        | 2.08  | 230  | 0.0773          |
| 0.0466        | 2.18  | 240  | 0.0589          |
| 0.0429        | 2.27  | 250  | 0.0684          |
| 0.0408        | 2.36  | 260  | 0.0617          |
| 0.0421        | 2.45  | 270  | 0.0640          |
| 0.0389        | 2.54  | 280  | 0.0633          |
| 0.0431        | 2.63  | 290  | 0.0594          |
| 0.0429        | 2.72  | 300  | 0.0616          |
| 0.0431        | 2.81  | 310  | 0.0616          |
| 0.0434        | 2.9   | 320  | 0.0604          |
| 0.046         | 2.99  | 330  | 0.0598          |


### Framework versions

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