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---
tags:
- generated_from_trainer
datasets:
- gokuls/wiki_book_corpus_complete_processed_bert_dataset
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v4_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: 0.2879346070609049
---
<!-- 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_v4_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: 4.7042
- Accuracy: 0.2879
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.5774 | 0.08 | 10000 | 6.5399 | 0.1253 |
| 6.3254 | 0.16 | 20000 | 6.3103 | 0.1388 |
| 6.2278 | 0.25 | 30000 | 6.2114 | 0.1443 |
| 6.1712 | 0.33 | 40000 | 6.1491 | 0.1475 |
| 6.12 | 0.41 | 50000 | 6.1086 | 0.1492 |
| 6.0914 | 0.49 | 60000 | 6.0781 | 0.1500 |
| 6.0676 | 0.57 | 70000 | 6.0540 | 0.1505 |
| 6.0492 | 0.66 | 80000 | 6.0345 | 0.1512 |
| 6.028 | 0.74 | 90000 | 6.0157 | 0.1516 |
| 5.9337 | 0.82 | 100000 | 5.8988 | 0.1533 |
| 5.7697 | 0.9 | 110000 | 5.7402 | 0.1654 |
| 5.6918 | 0.98 | 120000 | 5.6387 | 0.1777 |
| 5.6026 | 1.07 | 130000 | 5.5348 | 0.1910 |
| 5.5066 | 1.15 | 140000 | 5.4329 | 0.2035 |
| 5.4294 | 1.23 | 150000 | 5.3326 | 0.2144 |
| 5.3402 | 1.31 | 160000 | 5.2304 | 0.2270 |
| 5.2397 | 1.39 | 170000 | 5.1170 | 0.2406 |
| 5.1356 | 1.47 | 180000 | 4.9793 | 0.2564 |
| 5.0099 | 1.56 | 190000 | 4.8372 | 0.2730 |
| 4.885 | 1.64 | 200000 | 4.7058 | 0.2878 |
### Framework versions
- Transformers 4.33.3
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.13.3
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