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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- wikitext
model-index:
- name: run_2
  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_2

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: 0.9502

## 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: 0.0005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.4559        | 0.27  | 50   | 7.1236          |
| 6.8523        | 0.55  | 100  | 6.6676          |
| 6.6103        | 0.82  | 150  | 6.5582          |
| 6.2417        | 1.1   | 200  | 5.6994          |
| 4.9738        | 1.37  | 250  | 4.3440          |
| 4.1043        | 1.65  | 300  | 3.7804          |
| 3.4265        | 1.92  | 350  | 3.0136          |
| 2.7667        | 2.2   | 400  | 2.5318          |
| 2.3538        | 2.47  | 450  | 2.0903          |
| 1.9591        | 2.75  | 500  | 1.7367          |
| 1.6652        | 3.02  | 550  | 1.5016          |
| 1.4318        | 3.29  | 600  | 1.3162          |
| 1.275         | 3.57  | 650  | 1.1657          |
| 1.1553        | 3.84  | 700  | 1.0655          |
| 1.0629        | 4.12  | 750  | 1.0029          |
| 1.0029        | 4.39  | 800  | 0.9683          |
| 0.9881        | 4.67  | 850  | 0.9536          |
| 0.9779        | 4.94  | 900  | 0.9502          |


### Framework versions

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