---
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: 0.0107

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.6252        | 0.55  | 100  | 6.4113          |
| 4.839         | 1.1   | 200  | 2.0385          |
| 0.9137        | 1.65  | 300  | 0.3108          |
| 0.171         | 2.2   | 400  | 0.0877          |
| 0.0542        | 2.75  | 500  | 0.0396          |
| 0.025         | 3.29  | 600  | 0.0242          |
| 0.0148        | 3.84  | 700  | 0.0180          |
| 0.0098        | 4.39  | 800  | 0.0148          |
| 0.0077        | 4.94  | 900  | 0.0130          |
| 0.006         | 5.49  | 1000 | 0.0121          |
| 0.0053        | 6.04  | 1100 | 0.0115          |
| 0.0045        | 6.59  | 1200 | 0.0112          |
| 0.0042        | 7.14  | 1300 | 0.0110          |
| 0.0039        | 7.69  | 1400 | 0.0109          |
| 0.0038        | 8.24  | 1500 | 0.0108          |
| 0.0037        | 8.79  | 1600 | 0.0107          |
| 0.0037        | 9.33  | 1700 | 0.0107          |
| 0.0036        | 9.88  | 1800 | 0.0107          |


### Framework versions

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