---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0417MADP9
  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. -->

# V0417MADP9

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: 0.0671

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.3125        | 0.09  | 10   | 2.0178          |
| 3.6162        | 0.18  | 20   | 0.7351          |
| 1.6265        | 0.27  | 30   | 0.1559          |
| 0.7777        | 0.36  | 40   | 0.1366          |
| 0.1862        | 0.45  | 50   | 0.1302          |
| 0.1458        | 0.54  | 60   | 0.1170          |
| 0.1323        | 0.63  | 70   | 0.1083          |
| 0.1224        | 0.73  | 80   | 0.1041          |
| 0.1123        | 0.82  | 90   | 0.1013          |
| 0.1056        | 0.91  | 100  | 0.0898          |
| 0.1065        | 1.0   | 110  | 0.0886          |
| 0.0999        | 1.09  | 120  | 0.0858          |
| 0.1017        | 1.18  | 130  | 0.0830          |
| 0.1028        | 1.27  | 140  | 0.0838          |
| 0.1295        | 1.36  | 150  | 0.1006          |
| 0.1121        | 1.45  | 160  | 0.0873          |
| 0.1014        | 1.54  | 170  | 0.0844          |
| 0.0944        | 1.63  | 180  | 0.0777          |
| 0.0873        | 1.72  | 190  | 0.0776          |
| 0.0924        | 1.81  | 200  | 0.0747          |
| 0.0847        | 1.9   | 210  | 0.0727          |
| 0.0796        | 1.99  | 220  | 0.0727          |
| 0.075         | 2.08  | 230  | 0.0707          |
| 0.0789        | 2.18  | 240  | 0.0702          |
| 0.077         | 2.27  | 250  | 0.0710          |
| 0.0784        | 2.36  | 260  | 0.0692          |
| 0.0784        | 2.45  | 270  | 0.0689          |
| 0.072         | 2.54  | 280  | 0.0685          |
| 0.0697        | 2.63  | 290  | 0.0677          |
| 0.0735        | 2.72  | 300  | 0.0675          |
| 0.0751        | 2.81  | 310  | 0.0674          |
| 0.071         | 2.9   | 320  | 0.0672          |
| 0.0779        | 2.99  | 330  | 0.0671          |


### Framework versions

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