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# lang_adapter_fa_twitter_xlm_roberta_base_pfeiffer

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6701
- Accuracy: 0.6447

## 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: 5
- eval_batch_size: 5
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.0195        | 0.48  | 500   | 1.7864          | 0.6289   |
| 2.3543        | 0.95  | 1000  | 1.7252          | 0.6366   |
| 2.2612        | 1.43  | 1500  | 1.7230          | 0.6363   |
| 2.2055        | 1.9   | 2000  | 1.6968          | 0.6415   |
| 2.1811        | 2.38  | 2500  | 1.6875          | 0.6413   |
| 2.1813        | 2.85  | 3000  | 1.6890          | 0.6419   |
| 2.1657        | 3.33  | 3500  | 1.6684          | 0.6453   |
| 2.1375        | 3.81  | 4000  | 1.6591          | 0.6486   |
| 2.1516        | 4.28  | 4500  | 1.6674          | 0.6452   |
| 2.1363        | 4.76  | 5000  | 1.6691          | 0.6423   |
| 2.1235        | 5.23  | 5500  | 1.6573          | 0.6465   |
| 2.132         | 5.71  | 6000  | 1.6597          | 0.6433   |
| 2.1043        | 6.18  | 6500  | 1.6370          | 0.6521   |
| 2.127         | 6.66  | 7000  | 1.6723          | 0.6446   |
| 2.1116        | 7.14  | 7500  | 1.6521          | 0.6450   |
| 2.0916        | 7.61  | 8000  | 1.6538          | 0.6492   |
| 2.105         | 8.09  | 8500  | 1.6380          | 0.6492   |
| 2.0921        | 8.56  | 9000  | 1.6747          | 0.6429   |
| 2.0929        | 9.04  | 9500  | 1.6496          | 0.6449   |
| 2.0915        | 9.51  | 10000 | 1.6552          | 0.6460   |
| 2.0715        | 9.99  | 10500 | 1.6649          | 0.6444   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

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

lang\_adapter\_fa\_twitter\_xlm\_roberta\_base\_pfeiffer
========================================================


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


* Loss: 1.6701
* Accuracy: 0.6447


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: 5
* eval\_batch\_size: 5
* 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 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 5
* eval\_batch\_size: 5
* 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 0.13.2
TAGS
#tensorboard #generated_from_trainer #license-mit #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 5
* eval\_batch\_size: 5
* 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 0.13.2
TAGS
#tensorboard #generated_from_trainer #license-mit #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 5
* eval\_batch\_size: 5
* 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 0.13.2