---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0320MP6
  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. -->

# V0320MP6

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: 0.1245

## 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: 20
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5658        | 0.09  | 10   | 2.4014          |
| 2.2012        | 0.18  | 20   | 1.8503          |
| 1.6313        | 0.27  | 30   | 1.2804          |
| 1.1536        | 0.36  | 40   | 0.8569          |
| 0.7302        | 0.45  | 50   | 0.3937          |
| 0.3829        | 0.54  | 60   | 0.2028          |
| 0.2398        | 0.63  | 70   | 0.1611          |
| 0.2003        | 0.73  | 80   | 0.1476          |
| 0.1817        | 0.82  | 90   | 0.1419          |
| 0.1747        | 0.91  | 100  | 0.1384          |
| 0.1706        | 1.0   | 110  | 0.1359          |
| 0.1557        | 1.09  | 120  | 0.1340          |
| 0.1601        | 1.18  | 130  | 0.1327          |
| 0.1575        | 1.27  | 140  | 0.1314          |
| 0.1625        | 1.36  | 150  | 0.1304          |
| 0.1509        | 1.45  | 160  | 0.1293          |
| 0.1481        | 1.54  | 170  | 0.1286          |
| 0.1552        | 1.63  | 180  | 0.1275          |
| 0.1465        | 1.72  | 190  | 0.1267          |
| 0.1434        | 1.81  | 200  | 0.1268          |
| 0.1475        | 1.9   | 210  | 0.1260          |
| 0.1478        | 1.99  | 220  | 0.1253          |
| 0.147         | 2.08  | 230  | 0.1254          |
| 0.1438        | 2.18  | 240  | 0.1252          |
| 0.1443        | 2.27  | 250  | 0.1250          |
| 0.146         | 2.36  | 260  | 0.1249          |
| 0.1446        | 2.45  | 270  | 0.1246          |
| 0.1414        | 2.54  | 280  | 0.1247          |
| 0.1414        | 2.63  | 290  | 0.1245          |
| 0.1436        | 2.72  | 300  | 0.1247          |
| 0.1469        | 2.81  | 310  | 0.1246          |
| 0.143         | 2.9   | 320  | 0.1247          |
| 0.1456        | 2.99  | 330  | 0.1245          |


### Framework versions

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