---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- wikitext
model-index:
- name: run_3
  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. -->

# run_3

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the wikitext dataset.
It achieves the following results on the evaluation set:
- Loss: 7.1422

## 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: 0.005
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.8139        | 0.07  | 50   | 7.3922          |
| 7.3173        | 0.14  | 100  | 7.2946          |
| 7.2587        | 0.21  | 150  | 7.2339          |
| 7.2122        | 0.27  | 200  | 7.2167          |
| 7.1908        | 0.34  | 250  | 7.1945          |
| 7.171         | 0.41  | 300  | 7.1875          |
| 7.2054        | 0.48  | 350  | 7.1893          |
| 7.1899        | 0.55  | 400  | 7.1889          |
| 7.1839        | 0.62  | 450  | 7.1801          |
| 7.1571        | 0.69  | 500  | 7.1759          |
| 7.1577        | 0.75  | 550  | 7.1725          |
| 7.1799        | 0.82  | 600  | 7.1757          |
| 7.1698        | 0.89  | 650  | 7.1715          |
| 7.1705        | 0.96  | 700  | 7.1651          |
| 7.1712        | 1.03  | 750  | 7.1677          |
| 7.1418        | 1.1   | 800  | 7.1699          |
| 7.1692        | 1.17  | 850  | 7.1659          |
| 7.1376        | 1.24  | 900  | 7.1656          |
| 7.1703        | 1.3   | 950  | 7.1643          |
| 7.1534        | 1.37  | 1000 | 7.1676          |
| 7.1445        | 1.44  | 1050 | 7.1607          |
| 7.1552        | 1.51  | 1100 | 7.1596          |
| 7.1475        | 1.58  | 1150 | 7.1599          |
| 7.1401        | 1.65  | 1200 | 7.1593          |
| 7.161         | 1.72  | 1250 | 7.1606          |
| 7.1513        | 1.78  | 1300 | 7.1564          |
| 7.1465        | 1.85  | 1350 | 7.1548          |
| 7.1603        | 1.92  | 1400 | 7.1529          |
| 7.1203        | 1.99  | 1450 | 7.1533          |
| 7.1308        | 2.06  | 1500 | 7.1546          |
| 7.1244        | 2.13  | 1550 | 7.1546          |
| 7.1437        | 2.2   | 1600 | 7.1561          |
| 7.1618        | 2.26  | 1650 | 7.1517          |
| 7.1502        | 2.33  | 1700 | 7.1519          |
| 7.146         | 2.4   | 1750 | 7.1514          |
| 7.1088        | 2.47  | 1800 | 7.1520          |
| 7.1335        | 2.54  | 1850 | 7.1483          |
| 7.1388        | 2.61  | 1900 | 7.1472          |
| 7.1502        | 2.68  | 1950 | 7.1470          |
| 7.1511        | 2.75  | 2000 | 7.1479          |
| 7.1288        | 2.81  | 2050 | 7.1506          |
| 7.1416        | 2.88  | 2100 | 7.1488          |
| 7.1568        | 2.95  | 2150 | 7.1512          |
| 7.133         | 3.02  | 2200 | 7.1497          |
| 7.1178        | 3.09  | 2250 | 7.1501          |
| 7.1482        | 3.16  | 2300 | 7.1506          |
| 7.1242        | 3.23  | 2350 | 7.1504          |
| 7.1181        | 3.29  | 2400 | 7.1497          |
| 7.1133        | 3.36  | 2450 | 7.1495          |
| 7.1199        | 3.43  | 2500 | 7.1468          |
| 7.146         | 3.5   | 2550 | 7.1467          |
| 7.1284        | 3.57  | 2600 | 7.1455          |
| 7.1356        | 3.64  | 2650 | 7.1464          |
| 7.1372        | 3.71  | 2700 | 7.1445          |
| 7.1307        | 3.77  | 2750 | 7.1429          |
| 7.1407        | 3.84  | 2800 | 7.1427          |
| 7.126         | 3.91  | 2850 | 7.1426          |
| 7.1288        | 3.98  | 2900 | 7.1425          |
| 7.1223        | 4.05  | 2950 | 7.1428          |
| 7.1169        | 4.12  | 3000 | 7.1429          |
| 7.139         | 4.19  | 3050 | 7.1441          |
| 7.1231        | 4.26  | 3100 | 7.1433          |
| 7.1114        | 4.32  | 3150 | 7.1429          |
| 7.1204        | 4.39  | 3200 | 7.1429          |
| 7.0994        | 4.46  | 3250 | 7.1430          |
| 7.1039        | 4.53  | 3300 | 7.1434          |
| 7.1489        | 4.6   | 3350 | 7.1428          |
| 7.1315        | 4.67  | 3400 | 7.1426          |
| 7.1173        | 4.74  | 3450 | 7.1426          |
| 7.1241        | 4.8   | 3500 | 7.1428          |
| 7.1001        | 4.87  | 3550 | 7.1427          |
| 7.137         | 4.94  | 3600 | 7.1422          |


### Framework versions

- Transformers 4.33.1
- Pytorch 1.12.1
- Datasets 2.14.6
- Tokenizers 0.13.3