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# model

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [Europarl language detection](https://huggingface.co/datasets/simoneteglia/europarl_for_language_detection_10k) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0237
- Accuracy: 0.9967
- F1: 0.9967

## 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: 1e-05
- train_batch_size: 256
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 821  | 0.0270          | 0.9965   | 0.9965 |
| 0.2372        | 2.0   | 1642 | 0.0237          | 0.9967   | 0.9967 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
{"language": ["en", "it", "de", "nl", "lt", "es", "sv", "el", "pl", "sl", "hu", "bg", "fi", "pt", "sk", "da", "cs", "et", "lv", "ro", "fr"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["simoneteglia/europarl_for_language_detection_10k"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "model", "results": []}]}
transformers pytorch tensorboard safetensors xlm-roberta text-classification generated_from_trainer en it de nl lt es sv el pl sl hu bg fi pt sk da cs et lv ro fr dataset:simoneteglia/europarl_for_language_detection_10k license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #xlm-roberta #text-classification #generated_from_trainer #en #it #de #nl #lt #es #sv #el #pl #sl #hu #bg #fi #pt #sk #da #cs #et #lv #ro #fr #dataset-simoneteglia/europarl_for_language_detection_10k #license-mit #autotrain_compatible #endpoints_compatible #region-us 

model
=====


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


* Loss: 0.0237
* Accuracy: 0.9967
* F1: 0.9967


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: 1e-05
* train\_batch\_size: 256
* eval\_batch\_size: 512
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 256
* eval\_batch\_size: 512
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #xlm-roberta #text-classification #generated_from_trainer #en #it #de #nl #lt #es #sv #el #pl #sl #hu #bg #fi #pt #sk #da #cs #et #lv #ro #fr #dataset-simoneteglia/europarl_for_language_detection_10k #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 256
* eval\_batch\_size: 512
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3