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---
tags:
- generated_from_trainer
model-index:
- name: bert-pretrained-wikitext-2-raw-v1
results: []
license: apache-2.0
datasets:
- wikitext
language:
- en
metrics:
- accuracy
library_name: transformers
pipeline_tag: fill-mask
---
<!-- 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-pretrained-wikitext-2-raw-v1
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.9307
- Masked ml accuracy: 0.1485
- Nsp accuracy: 0.7891
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Masked ml accuracy | Nsp accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------------------:|:------------:|
| 7.9726 | 1.0 | 564 | 7.5680 | 0.1142 | 0.5 |
| 7.5085 | 2.0 | 1128 | 7.4155 | 0.1329 | 0.5557 |
| 7.4112 | 3.0 | 1692 | 7.3729 | 0.1380 | 0.5675 |
| 7.3352 | 4.0 | 2256 | 7.2816 | 0.1398 | 0.6060 |
| 7.2823 | 5.0 | 2820 | 7.1709 | 0.1414 | 0.6884 |
| 7.1828 | 6.0 | 3384 | 7.1503 | 0.1417 | 0.7109 |
| 7.0796 | 7.0 | 3948 | 7.0909 | 0.1431 | 0.7430 |
| 6.8699 | 8.0 | 4512 | 7.1666 | 0.1422 | 0.7238 |
| 6.7819 | 9.0 | 5076 | 7.2507 | 0.1467 | 0.7345 |
| 6.7269 | 10.0 | 5640 | 7.2654 | 0.1447 | 0.7484 |
| 6.6701 | 11.0 | 6204 | 7.3642 | 0.1439 | 0.7784 |
| 6.613 | 12.0 | 6768 | 7.5089 | 0.1447 | 0.7677 |
| 6.5577 | 13.0 | 7332 | 7.7611 | 0.1469 | 0.7655 |
| 6.5197 | 14.0 | 7896 | 7.5984 | 0.1465 | 0.7827 |
| 6.4626 | 15.0 | 8460 | 7.6738 | 0.1449 | 0.8030 |
| 6.4026 | 16.0 | 9024 | 7.7009 | 0.1457 | 0.7869 |
| 6.3861 | 17.0 | 9588 | 7.7586 | 0.1503 | 0.7955 |
| 6.3779 | 18.0 | 10152 | 7.7792 | 0.1494 | 0.8019 |
| 6.357 | 19.0 | 10716 | 7.8532 | 0.1479 | 0.7966 |
| 6.3354 | 20.0 | 11280 | 7.9307 | 0.1485 | 0.7891 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3 |