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# lang_adapter_fa_digikala_multilingual_base_cased

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:
- Loss: 1.8074
- Accuracy: 0.6254

## 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: 0.0001
- 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: 10.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.7072        | 0.45  | 500   | 2.3782          | 0.5341   |
| 2.4037        | 0.9   | 1000  | 2.2189          | 0.5588   |
| 2.2792        | 1.35  | 1500  | 2.1282          | 0.5720   |
| 2.2017        | 1.8   | 2000  | 2.0641          | 0.5821   |
| 2.1322        | 2.25  | 2500  | 2.0273          | 0.5889   |
| 2.0955        | 2.7   | 3000  | 1.9950          | 0.5945   |
| 2.0673        | 3.15  | 3500  | 1.9655          | 0.6000   |
| 2.0399        | 3.6   | 4000  | 1.9462          | 0.6033   |
| 2.0148        | 4.05  | 4500  | 1.9300          | 0.6056   |
| 1.9987        | 4.5   | 5000  | 1.9113          | 0.6069   |
| 1.9824        | 4.95  | 5500  | 1.8823          | 0.6128   |
| 1.9704        | 5.41  | 6000  | 1.8824          | 0.6119   |
| 1.9502        | 5.86  | 6500  | 1.8701          | 0.6157   |
| 1.9527        | 6.31  | 7000  | 1.8497          | 0.6190   |
| 1.9217        | 6.76  | 7500  | 1.8493          | 0.6174   |
| 1.9091        | 7.21  | 8000  | 1.8341          | 0.6210   |
| 1.9095        | 7.66  | 8500  | 1.8145          | 0.6250   |
| 1.9107        | 8.11  | 9000  | 1.8320          | 0.6190   |
| 1.8929        | 8.56  | 9500  | 1.8051          | 0.6268   |
| 1.8855        | 9.01  | 10000 | 1.8257          | 0.6221   |
| 1.8893        | 9.46  | 10500 | 1.8206          | 0.6231   |
| 1.8899        | 9.91  | 11000 | 1.7972          | 0.6244   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "lang_adapter_fa_digikala_multilingual_base_cased", "results": []}]}
tensorboard generated_from_trainer license:apache-2.0 region:us
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 

lang\_adapter\_fa\_digikala\_multilingual\_base\_cased
======================================================


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:


* Loss: 1.8074
* Accuracy: 0.6254


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: 0.0001
* 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: 10.0


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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: 10.0 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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: 10.0 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#tensorboard #generated_from_trainer #license-apache-2.0 #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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: 10.0### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.12.1