---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0503HMA6H
  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. -->

# V0503HMA6H

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: 0.0789

## 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: 80
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6387        | 0.09  | 10   | 0.1732          |
| 0.1418        | 0.18  | 20   | 0.1123          |
| 0.1121        | 0.27  | 30   | 0.0965          |
| 0.1028        | 0.36  | 40   | 0.0867          |
| 0.0843        | 0.45  | 50   | 0.0755          |
| 0.0873        | 0.54  | 60   | 0.0846          |
| 0.0852        | 0.63  | 70   | 0.0728          |
| 0.0829        | 0.73  | 80   | 0.1861          |
| 1.6498        | 0.82  | 90   | 0.1034          |
| 2.9198        | 0.91  | 100  | 2.6894          |
| 4.4394        | 1.0   | 110  | 2.1642          |
| 1.1969        | 1.09  | 120  | 0.5102          |
| 0.4174        | 1.18  | 130  | 0.3222          |
| 0.3113        | 1.27  | 140  | 0.2990          |
| 0.2566        | 1.36  | 150  | 0.2072          |
| 0.1857        | 1.45  | 160  | 0.1786          |
| 0.1804        | 1.54  | 170  | 0.1617          |
| 0.1623        | 1.63  | 180  | 0.1588          |
| 0.1511        | 1.72  | 190  | 0.1394          |
| 0.1353        | 1.81  | 200  | 0.1214          |
| 0.1185        | 1.9   | 210  | 0.1228          |
| 0.1201        | 1.99  | 220  | 0.1079          |
| 0.1073        | 2.08  | 230  | 0.1116          |
| 0.1001        | 2.18  | 240  | 0.0929          |
| 0.0964        | 2.27  | 250  | 0.0884          |
| 0.0897        | 2.36  | 260  | 0.0858          |
| 0.0862        | 2.45  | 270  | 0.0836          |
| 0.0866        | 2.54  | 280  | 0.0830          |
| 0.086         | 2.63  | 290  | 0.0805          |
| 0.0818        | 2.72  | 300  | 0.0786          |
| 0.084         | 2.81  | 310  | 0.0774          |
| 0.0802        | 2.9   | 320  | 0.0790          |
| 0.0759        | 2.99  | 330  | 0.0789          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1