---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- wikitext
model-index:
- name: run_4
  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_4

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: 0.2449

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 9.1704        | 0.27  | 50   | 8.0057          |
| 7.2118        | 0.55  | 100  | 6.6834          |
| 6.5244        | 0.82  | 150  | 6.3491          |
| 6.2201        | 1.1   | 200  | 6.0229          |
| 5.7189        | 1.37  | 250  | 5.1311          |
| 4.1268        | 1.65  | 300  | 2.9582          |
| 2.4963        | 1.92  | 350  | 1.7429          |
| 1.5611        | 2.2   | 400  | 1.0743          |
| 1.0537        | 2.47  | 450  | 0.7155          |
| 0.7665        | 2.75  | 500  | 0.5189          |
| 0.5947        | 3.02  | 550  | 0.4061          |
| 0.4782        | 3.29  | 600  | 0.3396          |
| 0.4161        | 3.57  | 650  | 0.2976          |
| 0.3785        | 3.84  | 700  | 0.2718          |
| 0.3491        | 4.12  | 750  | 0.2567          |
| 0.3319        | 4.39  | 800  | 0.2488          |
| 0.3286        | 4.67  | 850  | 0.2455          |
| 0.326         | 4.94  | 900  | 0.2449          |


### Framework versions

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