---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0320MP5
  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. -->

# V0320MP5

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: 0.1221

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5797        | 0.09  | 10   | 2.4043          |
| 2.2333        | 0.18  | 20   | 1.9404          |
| 1.7184        | 0.27  | 30   | 1.3622          |
| 1.2264        | 0.36  | 40   | 0.9245          |
| 0.7942        | 0.45  | 50   | 0.4516          |
| 0.4096        | 0.54  | 60   | 0.2127          |
| 0.2339        | 0.63  | 70   | 0.1601          |
| 0.1922        | 0.73  | 80   | 0.1446          |
| 0.1739        | 0.82  | 90   | 0.1388          |
| 0.1671        | 0.91  | 100  | 0.1353          |
| 0.1587        | 1.0   | 110  | 0.1330          |
| 0.1533        | 1.09  | 120  | 0.1316          |
| 0.1536        | 1.18  | 130  | 0.1302          |
| 0.1535        | 1.27  | 140  | 0.1290          |
| 0.1541        | 1.36  | 150  | 0.1279          |
| 0.1465        | 1.45  | 160  | 0.1269          |
| 0.1459        | 1.54  | 170  | 0.1260          |
| 0.1498        | 1.63  | 180  | 0.1251          |
| 0.1435        | 1.72  | 190  | 0.1241          |
| 0.138         | 1.81  | 200  | 0.1240          |
| 0.1407        | 1.9   | 210  | 0.1236          |
| 0.1409        | 1.99  | 220  | 0.1231          |
| 0.1445        | 2.08  | 230  | 0.1230          |
| 0.1408        | 2.18  | 240  | 0.1227          |
| 0.1381        | 2.27  | 250  | 0.1226          |
| 0.1395        | 2.36  | 260  | 0.1225          |
| 0.1447        | 2.45  | 270  | 0.1225          |
| 0.1366        | 2.54  | 280  | 0.1222          |
| 0.1365        | 2.63  | 290  | 0.1221          |
| 0.1409        | 2.72  | 300  | 0.1221          |
| 0.1413        | 2.81  | 310  | 0.1220          |
| 0.1435        | 2.9   | 320  | 0.1221          |
| 0.1421        | 2.99  | 330  | 0.1221          |


### Framework versions

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