---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0414H2
  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. -->

# V0414H2

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: 0.0460

## 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: 0.003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.149         | 0.05  | 10   | 1.1737          |
| 0.4718        | 0.09  | 20   | 0.1474          |
| 0.1443        | 0.14  | 30   | 0.1201          |
| 0.1135        | 0.18  | 40   | 0.0995          |
| 0.0994        | 0.23  | 50   | 0.0855          |
| 0.1011        | 0.27  | 60   | 0.0916          |
| 0.0941        | 0.32  | 70   | 0.0861          |
| 0.097         | 0.36  | 80   | 0.0793          |
| 0.0799        | 0.41  | 90   | 0.0790          |
| 0.0896        | 0.45  | 100  | 0.0803          |
| 0.0904        | 0.5   | 110  | 0.0796          |
| 0.0918        | 0.54  | 120  | 0.0736          |
| 0.081         | 0.59  | 130  | 0.0717          |
| 0.0785        | 0.63  | 140  | 0.0730          |
| 0.0765        | 0.68  | 150  | 0.0761          |
| 0.0823        | 0.73  | 160  | 0.0772          |
| 0.0809        | 0.77  | 170  | 0.0706          |
| 0.0836        | 0.82  | 180  | 0.0858          |
| 0.0991        | 0.86  | 190  | 0.0790          |
| 0.0788        | 0.91  | 200  | 0.0770          |
| 0.0939        | 0.95  | 210  | 0.0734          |
| 0.0891        | 1.0   | 220  | 0.0741          |
| 0.0704        | 1.04  | 230  | 0.0831          |
| 0.0833        | 1.09  | 240  | 0.0766          |
| 0.0777        | 1.13  | 250  | 0.0752          |
| 0.0723        | 1.18  | 260  | 0.0763          |
| 0.0803        | 1.22  | 270  | 0.0738          |
| 0.0694        | 1.27  | 280  | 0.0800          |
| 0.0894        | 1.31  | 290  | 0.0728          |
| 0.0891        | 1.36  | 300  | 0.0888          |
| 0.088         | 1.41  | 310  | 0.0712          |
| 0.0759        | 1.45  | 320  | 0.0709          |
| 0.0876        | 1.5   | 330  | 0.0695          |
| 0.0741        | 1.54  | 340  | 0.0770          |
| 0.0805        | 1.59  | 350  | 0.0683          |
| 0.0713        | 1.63  | 360  | 0.0739          |
| 0.0884        | 1.68  | 370  | 0.0816          |
| 0.083         | 1.72  | 380  | 0.0620          |
| 0.0665        | 1.77  | 390  | 0.0613          |
| 0.0718        | 1.81  | 400  | 0.0674          |
| 0.0655        | 1.86  | 410  | 0.0551          |
| 0.0517        | 1.9   | 420  | 0.0510          |
| 0.0532        | 1.95  | 430  | 0.0491          |
| 0.0537        | 1.99  | 440  | 0.0470          |
| 0.0483        | 2.04  | 450  | 0.0474          |
| 0.0337        | 2.08  | 460  | 0.0513          |
| 0.0361        | 2.13  | 470  | 0.0566          |
| 0.0464        | 2.18  | 480  | 0.0654          |
| 0.0509        | 2.22  | 490  | 0.0524          |
| 0.0425        | 2.27  | 500  | 0.0502          |
| 0.0421        | 2.31  | 510  | 0.0500          |
| 0.0351        | 2.36  | 520  | 0.0512          |
| 0.039         | 2.4   | 530  | 0.0486          |
| 0.0477        | 2.45  | 540  | 0.0484          |
| 0.0425        | 2.49  | 550  | 0.0459          |
| 0.0461        | 2.54  | 560  | 0.0455          |
| 0.0413        | 2.58  | 570  | 0.0460          |
| 0.0546        | 2.63  | 580  | 0.0455          |
| 0.0344        | 2.67  | 590  | 0.0455          |
| 0.0362        | 2.72  | 600  | 0.0458          |
| 0.0373        | 2.76  | 610  | 0.0459          |
| 0.0379        | 2.81  | 620  | 0.0461          |
| 0.0459        | 2.86  | 630  | 0.0461          |
| 0.0386        | 2.9   | 640  | 0.0460          |
| 0.0346        | 2.95  | 650  | 0.0460          |
| 0.0277        | 2.99  | 660  | 0.0460          |


### Framework versions

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