
<!-- 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-base-multilingual-cased-Confusion-mlm-20230604

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.8295
- Loss: 0.6294

## 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: 8
- eval_batch_size: 8
- 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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.732         | 1.0   | 130  | 0.8361   | 0.5171          |
| 0.6489        | 2.0   | 260  | 0.8421   | 0.6181          |
| 0.7594        | 3.0   | 390  | 0.8474   | 0.5202          |
| 0.7408        | 4.0   | 520  | 0.8212   | 0.7330          |
| 0.7802        | 5.0   | 650  | 0.8562   | 0.6039          |
| 0.7458        | 6.0   | 780  | 0.7885   | 0.7175          |
| 0.6875        | 7.0   | 910  | 0.8247   | 0.5894          |
| 0.6826        | 8.0   | 1040 | 0.7943   | 0.7404          |
| 0.6979        | 9.0   | 1170 | 0.8370   | 0.5288          |
| 0.6011        | 10.0  | 1300 | 0.8227   | 0.7400          |
| 0.5925        | 11.0  | 1430 | 0.8333   | 0.6346          |
| 0.6168        | 12.0  | 1560 | 0.8509   | 0.5866          |
| 0.5798        | 13.0  | 1690 | 0.8012   | 0.7777          |
| 0.5861        | 14.0  | 1820 | 0.8108   | 0.6529          |
| 0.53          | 15.0  | 1950 | 0.8297   | 0.5617          |
| 0.5992        | 16.0  | 2080 | 0.8505   | 0.5977          |
| 0.5424        | 17.0  | 2210 | 0.8359   | 0.5167          |
| 0.567         | 18.0  | 2340 | 0.8585   | 0.4843          |
| 0.4832        | 19.0  | 2470 | 0.8799   | 0.4312          |
| 0.4914        | 20.0  | 2600 | 0.8295   | 0.6294          |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert-base-multilingual-cased-Confusion-mlm-20230604", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-base-multilingual-cased-Confusion-mlm-20230604
===================================================


This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Accuracy: 0.8295
* Loss: 0.6294


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3