---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA21
  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. -->

# V0424HMA21

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: 0.0510

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7087        | 0.09  | 10   | 0.1473          |
| 0.1506        | 0.18  | 20   | 0.1108          |
| 0.1133        | 0.27  | 30   | 0.1019          |
| 0.1011        | 0.36  | 40   | 0.0782          |
| 0.0812        | 0.45  | 50   | 0.0733          |
| 0.0826        | 0.54  | 60   | 0.0711          |
| 0.078         | 0.63  | 70   | 0.0749          |
| 0.0795        | 0.73  | 80   | 0.0884          |
| 0.0828        | 0.82  | 90   | 0.0764          |
| 0.0862        | 0.91  | 100  | 0.2925          |
| 0.139         | 1.0   | 110  | 0.0806          |
| 0.0759        | 1.09  | 120  | 0.1017          |
| 0.1034        | 1.18  | 130  | 0.0768          |
| 0.0777        | 1.27  | 140  | 0.0675          |
| 0.0737        | 1.36  | 150  | 0.0729          |
| 0.0768        | 1.45  | 160  | 0.0766          |
| 0.0768        | 1.54  | 170  | 0.0676          |
| 0.0689        | 1.63  | 180  | 0.0659          |
| 0.0599        | 1.72  | 190  | 0.0638          |
| 0.0599        | 1.81  | 200  | 0.0603          |
| 0.0503        | 1.9   | 210  | 0.0587          |
| 0.0444        | 1.99  | 220  | 0.0525          |
| 0.0275        | 2.08  | 230  | 0.0535          |
| 0.0215        | 2.18  | 240  | 0.0584          |
| 0.0207        | 2.27  | 250  | 0.0554          |
| 0.0205        | 2.36  | 260  | 0.0547          |
| 0.0244        | 2.45  | 270  | 0.0533          |
| 0.023         | 2.54  | 280  | 0.0511          |
| 0.0192        | 2.63  | 290  | 0.0521          |
| 0.0183        | 2.72  | 300  | 0.0516          |
| 0.0236        | 2.81  | 310  | 0.0512          |
| 0.0212        | 2.9   | 320  | 0.0510          |
| 0.0189        | 2.99  | 330  | 0.0510          |


### Framework versions

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