pytorch tensorboard bert fill-mask transformers generated_from_trainer model-index autotrain_compatible
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-juman-bpe
  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. -->

# bert-small-juman-bpe

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.6317
- Loss: 1.7829

## 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: 0.0001
- train_batch_size: 256
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 768
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 14
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Accuracy | Validation Loss |
|:-------------:|:-----:|:------:|:--------:|:---------------:|
| 2.3892        | 1.0   | 69472  | 0.5637   | 2.2498          |
| 2.2219        | 2.0   | 138944 | 0.5873   | 2.0785          |
| 2.1453        | 3.0   | 208416 | 0.5984   | 2.0019          |
| 2.1           | 4.0   | 277888 | 0.6059   | 1.9531          |
| 2.068         | 5.0   | 347360 | 0.6106   | 1.9169          |
| 2.0405        | 6.0   | 416832 | 0.6146   | 1.8921          |
| 2.0174        | 7.0   | 486304 | 0.6175   | 1.8711          |
| 2.0002        | 8.0   | 555776 | 0.6205   | 1.8527          |
| 1.9838        | 9.0   | 625248 | 0.6225   | 1.8381          |
| 1.9691        | 10.0  | 694720 | 0.6248   | 1.8239          |
| 1.9551        | 11.0  | 764192 | 0.6265   | 1.8125          |
| 1.9406        | 12.0  | 833664 | 0.6288   | 1.8002          |
| 1.9293        | 13.0  | 903136 | 0.6310   | 1.7871          |
| 1.9247        | 14.0  | 972608 | 0.6317   | 1.7829          |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.2.2
- Tokenizers 0.12.1
