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

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: 0.2727

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 9.1471        | 0.55  | 50   | 7.9703          |
| 7.1714        | 1.1   | 100  | 6.6558          |
| 6.4707        | 1.65  | 150  | 6.2924          |
| 6.072         | 2.19  | 200  | 5.8048          |
| 5.1389        | 2.74  | 250  | 3.8826          |
| 3.1897        | 3.29  | 300  | 2.3133          |
| 1.9697        | 3.84  | 350  | 1.4230          |
| 1.2783        | 4.39  | 400  | 0.9488          |
| 0.8952        | 4.94  | 450  | 0.6810          |
| 0.6593        | 5.49  | 500  | 0.5228          |
| 0.5278        | 6.04  | 550  | 0.4249          |
| 0.4339        | 6.58  | 600  | 0.3630          |
| 0.3809        | 7.13  | 650  | 0.3237          |
| 0.3443        | 7.68  | 700  | 0.2991          |
| 0.3212        | 8.23  | 750  | 0.2843          |
| 0.3094        | 8.78  | 800  | 0.2765          |
| 0.3033        | 9.33  | 850  | 0.2734          |
| 0.3           | 9.88  | 900  | 0.2727          |


### Framework versions

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