---
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: 0.0165

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.562         | 0.55  | 50   | 6.9697          |
| 6.63          | 1.1   | 100  | 6.3436          |
| 5.938         | 1.65  | 150  | 5.1110          |
| 3.0597        | 2.19  | 200  | 1.4150          |
| 0.7989        | 2.74  | 250  | 0.3477          |
| 0.2227        | 3.29  | 300  | 0.1284          |
| 0.0925        | 3.84  | 350  | 0.0640          |
| 0.0475        | 4.39  | 400  | 0.0412          |
| 0.0314        | 4.94  | 450  | 0.0304          |
| 0.0217        | 5.49  | 500  | 0.0246          |
| 0.0181        | 6.04  | 550  | 0.0215          |
| 0.0146        | 6.58  | 600  | 0.0194          |
| 0.0132        | 7.13  | 650  | 0.0182          |
| 0.012         | 7.68  | 700  | 0.0174          |
| 0.0114        | 8.23  | 750  | 0.0169          |
| 0.011         | 8.78  | 800  | 0.0167          |
| 0.0108        | 9.33  | 850  | 0.0166          |
| 0.0106        | 9.88  | 900  | 0.0165          |


### Framework versions

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