---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0424HMA12
  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. -->

# V0424HMA12

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: 0.1319

## 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5164        | 0.09  | 10   | 0.1470          |
| 0.1523        | 0.18  | 20   | 0.1190          |
| 0.1124        | 0.27  | 30   | 0.0974          |
| 0.1056        | 0.36  | 40   | 0.0875          |
| 0.0798        | 0.45  | 50   | 0.0797          |
| 0.0884        | 0.54  | 60   | 0.0825          |
| 0.0851        | 0.63  | 70   | 0.0749          |
| 0.084         | 0.73  | 80   | 0.1080          |
| 0.1024        | 0.82  | 90   | 0.0820          |
| 0.342         | 0.91  | 100  | 0.1022          |
| 0.1777        | 1.0   | 110  | 0.1201          |
| 1.1335        | 1.09  | 120  | 10.0693         |
| 3.546         | 1.18  | 130  | 0.4678          |
| 0.5922        | 1.27  | 140  | 0.2032          |
| 0.293         | 1.36  | 150  | 0.1823          |
| 0.175         | 1.45  | 160  | 0.1510          |
| 0.1651        | 1.54  | 170  | 0.1670          |
| 0.1582        | 1.63  | 180  | 0.1542          |
| 0.1492        | 1.72  | 190  | 0.1420          |
| 0.1409        | 1.81  | 200  | 0.1404          |
| 0.1462        | 1.9   | 210  | 0.1417          |
| 0.1428        | 1.99  | 220  | 0.1407          |
| 0.1498        | 2.08  | 230  | 0.1731          |
| 0.1461        | 2.18  | 240  | 0.1394          |
| 0.1378        | 2.27  | 250  | 0.1333          |
| 0.1357        | 2.36  | 260  | 0.1321          |
| 0.1294        | 2.45  | 270  | 0.1322          |
| 0.1339        | 2.54  | 280  | 0.1312          |
| 0.131         | 2.63  | 290  | 0.1330          |
| 0.132         | 2.72  | 300  | 0.1361          |
| 0.1369        | 2.81  | 310  | 0.1319          |
| 0.1348        | 2.9   | 320  | 0.1317          |
| 0.1309        | 2.99  | 330  | 0.1319          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1