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# bert-base-multilingual-cased-Confusion-mlm-20230605

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: 0.5221
- Loss: 1.8989

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log        | 1.0   | 130  | 0.3587   | 2.8610          |
| No log        | 2.0   | 260  | 0.4649   | 2.3133          |
| No log        | 3.0   | 390  | 0.4307   | 2.4230          |
| 2.6029        | 4.0   | 520  | 0.4893   | 2.3436          |
| 2.6029        | 5.0   | 650  | 0.525    | 2.0247          |
| 2.6029        | 6.0   | 780  | 0.5116   | 2.1448          |
| 2.6029        | 7.0   | 910  | 0.5043   | 2.0569          |
| 2.0943        | 8.0   | 1040 | 0.5601   | 1.8873          |
| 2.0943        | 9.0   | 1170 | 0.5206   | 1.9879          |
| 2.0943        | 10.0  | 1300 | 0.5358   | 2.0974          |
| 2.0943        | 11.0  | 1430 | 0.5060   | 2.0974          |
| 1.8388        | 12.0  | 1560 | 0.5839   | 1.6869          |
| 1.8388        | 13.0  | 1690 | 0.5706   | 1.8915          |
| 1.8388        | 14.0  | 1820 | 0.5620   | 1.7826          |
| 1.8388        | 15.0  | 1950 | 0.5274   | 2.0275          |
| 1.7158        | 16.0  | 2080 | 0.5627   | 1.8270          |
| 1.7158        | 17.0  | 2210 | 0.5425   | 2.0630          |
| 1.7158        | 18.0  | 2340 | 0.5884   | 1.6747          |
| 1.7158        | 19.0  | 2470 | 0.55     | 1.8877          |
| 1.5481        | 20.0  | 2600 | 0.5221   | 1.8989          |


### 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-20230605", "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-20230605
===================================================


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: 0.5221
* Loss: 1.8989


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