---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0422MADP6C
  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. -->

# V0422MADP6C

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: 0.0637

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.2356        | 0.09  | 10   | 1.9434          |
| 2.8956        | 0.18  | 20   | 0.1595          |
| 0.6107        | 0.27  | 30   | 0.1437          |
| 0.1936        | 0.36  | 40   | 0.1236          |
| 0.1283        | 0.45  | 50   | 0.1001          |
| 0.1141        | 0.54  | 60   | 0.0983          |
| 0.1042        | 0.63  | 70   | 0.0888          |
| 0.089         | 0.73  | 80   | 0.0854          |
| 0.0922        | 0.82  | 90   | 0.0815          |
| 0.0892        | 0.91  | 100  | 0.0750          |
| 0.0853        | 1.0   | 110  | 0.0789          |
| 0.0755        | 1.09  | 120  | 0.0722          |
| 0.0795        | 1.18  | 130  | 0.0764          |
| 0.0794        | 1.27  | 140  | 0.0783          |
| 0.0711        | 1.36  | 150  | 0.0753          |
| 0.0717        | 1.45  | 160  | 0.0720          |
| 0.067         | 1.54  | 170  | 0.0739          |
| 0.0688        | 1.63  | 180  | 0.0712          |
| 0.0654        | 1.72  | 190  | 0.0699          |
| 0.0694        | 1.81  | 200  | 0.0652          |
| 0.0621        | 1.9   | 210  | 0.0680          |
| 0.0661        | 1.99  | 220  | 0.0654          |
| 0.0515        | 2.08  | 230  | 0.0617          |
| 0.0513        | 2.18  | 240  | 0.0650          |
| 0.0462        | 2.27  | 250  | 0.0725          |
| 0.0491        | 2.36  | 260  | 0.0693          |
| 0.0538        | 2.45  | 270  | 0.0697          |
| 0.0507        | 2.54  | 280  | 0.0663          |
| 0.0437        | 2.63  | 290  | 0.0642          |
| 0.0489        | 2.72  | 300  | 0.0635          |
| 0.0485        | 2.81  | 310  | 0.0637          |
| 0.0456        | 2.9   | 320  | 0.0637          |
| 0.0557        | 2.99  | 330  | 0.0637          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1