---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA26
  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. -->

# V0424HMA26

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: 0.0706

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5067        | 0.09  | 10   | 0.1397          |
| 0.1485        | 0.18  | 20   | 0.1057          |
| 0.1038        | 0.27  | 30   | 0.0912          |
| 0.0895        | 0.36  | 40   | 0.0768          |
| 0.0832        | 0.45  | 50   | 0.0716          |
| 0.085         | 0.54  | 60   | 0.0725          |
| 0.0765        | 0.63  | 70   | 0.0681          |
| 0.0702        | 0.73  | 80   | 0.0656          |
| 0.0736        | 0.82  | 90   | 0.0668          |
| 0.0792        | 0.91  | 100  | 0.0605          |
| 0.0774        | 1.0   | 110  | 0.0694          |
| 0.0591        | 1.09  | 120  | 0.0754          |
| 0.0665        | 1.18  | 130  | 0.0804          |
| 0.0707        | 1.27  | 140  | 0.0676          |
| 0.0618        | 1.36  | 150  | 0.0694          |
| 0.0661        | 1.45  | 160  | 0.0681          |
| 0.0584        | 1.54  | 170  | 0.0812          |
| 0.0617        | 1.63  | 180  | 0.0667          |
| 0.0519        | 1.72  | 190  | 0.0681          |
| 0.0666        | 1.81  | 200  | 0.0688          |
| 0.0553        | 1.9   | 210  | 0.0698          |
| 0.0513        | 1.99  | 220  | 0.0691          |
| 0.0371        | 2.08  | 230  | 0.0675          |
| 0.0325        | 2.18  | 240  | 0.0770          |
| 0.0276        | 2.27  | 250  | 0.0784          |
| 0.0317        | 2.36  | 260  | 0.0759          |
| 0.0314        | 2.45  | 270  | 0.0726          |
| 0.0291        | 2.54  | 280  | 0.0684          |
| 0.0262        | 2.63  | 290  | 0.0697          |
| 0.0264        | 2.72  | 300  | 0.0712          |
| 0.0322        | 2.81  | 310  | 0.0711          |
| 0.0289        | 2.9   | 320  | 0.0707          |
| 0.0304        | 2.99  | 330  | 0.0706          |


### Framework versions

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