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# distilbert-base-multilingual-cased-distilbert_mlm-20230603

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.9199
- Loss: 0.3297

## 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  | 0.9035   | 0.3341          |
| No log        | 2.0   | 260  | 0.9288   | 0.2137          |
| No log        | 3.0   | 390  | 0.9150   | 0.3078          |
| 0.3659        | 4.0   | 520  | 0.9301   | 0.3323          |
| 0.3659        | 5.0   | 650  | 0.8896   | 0.4231          |
| 0.3659        | 6.0   | 780  | 0.9414   | 0.2144          |
| 0.3659        | 7.0   | 910  | 0.9333   | 0.2529          |
| 0.3935        | 8.0   | 1040 | 0.9192   | 0.2802          |
| 0.3935        | 9.0   | 1170 | 0.9274   | 0.3097          |
| 0.3935        | 10.0  | 1300 | 0.9182   | 0.3077          |
| 0.3935        | 11.0  | 1430 | 0.9153   | 0.2983          |
| 0.3835        | 12.0  | 1560 | 0.9136   | 0.2692          |
| 0.3835        | 13.0  | 1690 | 0.9524   | 0.1930          |
| 0.3835        | 14.0  | 1820 | 0.9412   | 0.2278          |
| 0.3835        | 15.0  | 1950 | 0.9657   | 0.1305          |
| 0.3327        | 16.0  | 2080 | 0.8980   | 0.3051          |
| 0.3327        | 17.0  | 2210 | 0.9485   | 0.1348          |
| 0.3327        | 18.0  | 2340 | 0.9381   | 0.2765          |
| 0.3327        | 19.0  | 2470 | 0.9477   | 0.2165          |
| 0.3238        | 20.0  | 2600 | 0.9199   | 0.3297          |


### 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": "distilbert-base-multilingual-cased-distilbert_mlm-20230603", "results": []}]}
transformers pytorch tensorboard distilbert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-multilingual-cased-distilbert\_mlm-20230603
===========================================================


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


* Accuracy: 0.9199
* Loss: 0.3297


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 #distilbert #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