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# bert-base-multilingual-cased-Confusion-mlm-20230603

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: 0.5723
- Loss: 1.7609

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 3.2882        | 1.0   | 130  | 0.3554   | 2.9429          |
| 2.8803        | 2.0   | 260  | 0.3761   | 2.6740          |
| 2.6044        | 3.0   | 390  | 0.4656   | 2.2735          |
| 2.3907        | 4.0   | 520  | 0.4721   | 2.3350          |
| 2.2612        | 5.0   | 650  | 0.5242   | 2.0715          |
| 2.1133        | 6.0   | 780  | 0.4984   | 2.1209          |
| 2.1048        | 7.0   | 910  | 0.4960   | 2.0021          |
| 1.9521        | 8.0   | 1040 | 0.5224   | 2.2426          |
| 1.9255        | 9.0   | 1170 | 0.5472   | 1.8786          |
| 1.8923        | 10.0  | 1300 | 0.5364   | 1.9918          |
| 1.8296        | 11.0  | 1430 | 0.4738   | 2.2351          |
| 1.7689        | 12.0  | 1560 | 0.5028   | 2.0691          |
| 1.736         | 13.0  | 1690 | 0.5794   | 1.9221          |
| 1.7639        | 14.0  | 1820 | 0.5252   | 2.0188          |
| 1.6555        | 15.0  | 1950 | 0.6012   | 1.6560          |
| 1.6019        | 16.0  | 2080 | 0.5935   | 1.6369          |
| 1.5524        | 17.0  | 2210 | 0.6226   | 1.6262          |
| 1.5182        | 18.0  | 2340 | 0.6211   | 1.7780          |
| 1.5537        | 19.0  | 2470 | 0.5616   | 1.9577          |
| 1.5651        | 20.0  | 2600 | 0.5723   | 1.7609          |


### 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-20230603", "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-20230603
===================================================


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: 0.5723
* Loss: 1.7609


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