transformers pytorch bert fill-mask generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: checkpoint
  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. -->

# checkpoint

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2864

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 1.0   | 409   | 0.2613          |
| 0.6652        | 2.0   | 818   | 0.2190          |
| 0.2232        | 3.0   | 1227  | 0.2003          |
| 0.1932        | 4.0   | 1636  | 0.1924          |
| 0.1768        | 5.0   | 2045  | 0.1842          |
| 0.1768        | 6.0   | 2454  | 0.1817          |
| 0.1608        | 7.0   | 2863  | 0.1786          |
| 0.149         | 8.0   | 3272  | 0.1733          |
| 0.1391        | 9.0   | 3681  | 0.1799          |
| 0.1302        | 10.0  | 4090  | 0.1791          |
| 0.1302        | 11.0  | 4499  | 0.1798          |
| 0.1205        | 12.0  | 4908  | 0.1780          |
| 0.1115        | 13.0  | 5317  | 0.1823          |
| 0.1029        | 14.0  | 5726  | 0.1866          |
| 0.0963        | 15.0  | 6135  | 0.1865          |
| 0.0894        | 16.0  | 6544  | 0.1924          |
| 0.0894        | 17.0  | 6953  | 0.1956          |
| 0.0813        | 18.0  | 7362  | 0.1973          |
| 0.0755        | 19.0  | 7771  | 0.2012          |
| 0.0687        | 20.0  | 8180  | 0.2065          |
| 0.0634        | 21.0  | 8589  | 0.2090          |
| 0.0634        | 22.0  | 8998  | 0.2139          |
| 0.0575        | 23.0  | 9407  | 0.2161          |
| 0.0527        | 24.0  | 9816  | 0.2207          |
| 0.048         | 25.0  | 10225 | 0.2255          |
| 0.0447        | 26.0  | 10634 | 0.2277          |
| 0.0408        | 27.0  | 11043 | 0.2326          |
| 0.0408        | 28.0  | 11452 | 0.2378          |
| 0.0367        | 29.0  | 11861 | 0.2407          |
| 0.0337        | 30.0  | 12270 | 0.2458          |
| 0.0311        | 31.0  | 12679 | 0.2482          |
| 0.029         | 32.0  | 13088 | 0.2517          |
| 0.029         | 33.0  | 13497 | 0.2558          |
| 0.0268        | 34.0  | 13906 | 0.2628          |
| 0.0245        | 35.0  | 14315 | 0.2611          |
| 0.0229        | 36.0  | 14724 | 0.2658          |
| 0.0213        | 37.0  | 15133 | 0.2680          |
| 0.02          | 38.0  | 15542 | 0.2703          |
| 0.02          | 39.0  | 15951 | 0.2731          |
| 0.0185        | 40.0  | 16360 | 0.2763          |
| 0.0172        | 41.0  | 16769 | 0.2769          |
| 0.0165        | 42.0  | 17178 | 0.2810          |
| 0.0151        | 43.0  | 17587 | 0.2812          |
| 0.0151        | 44.0  | 17996 | 0.2807          |
| 0.0147        | 45.0  | 18405 | 0.2831          |
| 0.0142        | 46.0  | 18814 | 0.2849          |
| 0.0142        | 47.0  | 19223 | 0.2856          |
| 0.0131        | 48.0  | 19632 | 0.2856          |
| 0.0127        | 49.0  | 20041 | 0.2861          |
| 0.0127        | 50.0  | 20450 | 0.2864          |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
