---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0415B2
  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. -->

# V0415B2

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: 0.0627

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7796        | 0.09  | 10   | 2.7689          |
| 2.7682        | 0.18  | 20   | 2.7065          |
| 2.6102        | 0.27  | 30   | 2.3490          |
| 2.084         | 0.36  | 40   | 1.5865          |
| 1.2444        | 0.45  | 50   | 0.6290          |
| 0.3515        | 0.54  | 60   | 0.1070          |
| 0.1138        | 0.63  | 70   | 0.0952          |
| 0.1011        | 0.73  | 80   | 0.0862          |
| 0.0923        | 0.82  | 90   | 0.0828          |
| 0.0889        | 0.91  | 100  | 0.0770          |
| 0.0881        | 1.0   | 110  | 0.0754          |
| 0.0808        | 1.09  | 120  | 0.0727          |
| 0.082         | 1.18  | 130  | 0.0707          |
| 0.0819        | 1.27  | 140  | 0.0689          |
| 0.0743        | 1.36  | 150  | 0.0680          |
| 0.0812        | 1.45  | 160  | 0.0669          |
| 0.0735        | 1.54  | 170  | 0.0655          |
| 0.0763        | 1.63  | 180  | 0.0655          |
| 0.077         | 1.72  | 190  | 0.0650          |
| 0.0754        | 1.81  | 200  | 0.0638          |
| 0.0667        | 1.9   | 210  | 0.0636          |
| 0.0687        | 1.99  | 220  | 0.0646          |
| 0.0653        | 2.08  | 230  | 0.0642          |
| 0.0697        | 2.18  | 240  | 0.0638          |
| 0.0658        | 2.27  | 250  | 0.0632          |
| 0.0696        | 2.36  | 260  | 0.0633          |
| 0.0653        | 2.45  | 270  | 0.0631          |
| 0.0625        | 2.54  | 280  | 0.0629          |
| 0.0615        | 2.63  | 290  | 0.0630          |
| 0.0681        | 2.72  | 300  | 0.0629          |
| 0.0755        | 2.81  | 310  | 0.0628          |
| 0.0641        | 2.9   | 320  | 0.0628          |
| 0.0705        | 2.99  | 330  | 0.0627          |


### Framework versions

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