---
tags:
- generated_from_trainer
datasets:
- gokuls/wiki_book_corpus_complete_processed_bert_dataset
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v3_complete_training_48
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: gokuls/wiki_book_corpus_complete_processed_bert_dataset
      type: gokuls/wiki_book_corpus_complete_processed_bert_dataset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.44304308255003333
---

<!-- 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. -->

# bert_12_layer_model_v3_complete_training_48

This model is a fine-tuned version of [](https://huggingface.co/) on the gokuls/wiki_book_corpus_complete_processed_bert_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2767
- Accuracy: 0.4430

## 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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.5785        | 0.08  | 10000  | 6.5368          | 0.1282   |
| 6.3475        | 0.16  | 20000  | 6.3341          | 0.1409   |
| 6.2664        | 0.25  | 30000  | 6.2525          | 0.1446   |
| 6.2198        | 0.33  | 40000  | 6.2002          | 0.1474   |
| 6.1403        | 0.41  | 50000  | 6.1243          | 0.1497   |
| 6.0674        | 0.49  | 60000  | 6.0389          | 0.1520   |
| 5.9921        | 0.57  | 70000  | 5.9584          | 0.1548   |
| 5.9337        | 0.66  | 80000  | 5.8929          | 0.1577   |
| 5.8269        | 0.74  | 90000  | 5.7654          | 0.1685   |
| 5.5053        | 0.82  | 100000 | 5.3216          | 0.2274   |
| 4.8237        | 0.9   | 110000 | 4.6350          | 0.3054   |
| 4.3302        | 0.98  | 120000 | 4.1723          | 0.3496   |
| 4.0721        | 1.07  | 130000 | 3.9373          | 0.3741   |
| 3.8896        | 1.15  | 140000 | 3.7763          | 0.3903   |
| 3.7842        | 1.23  | 150000 | 3.6628          | 0.4018   |
| 3.6871        | 1.31  | 160000 | 3.5734          | 0.4111   |
| 3.6099        | 1.39  | 170000 | 3.4986          | 0.4188   |
| 3.5585        | 1.47  | 180000 | 3.4324          | 0.4259   |
| 3.4922        | 1.56  | 190000 | 3.3767          | 0.4316   |
| 3.4342        | 1.64  | 200000 | 3.3234          | 0.4374   |
| 3.3799        | 1.72  | 210000 | 3.2770          | 0.4429   |


### Framework versions

- Transformers 4.33.3
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.13.3