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# xlm-roberta-base-finetuned-language-detection

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5624
- Accuracy: 0.8195
- F1: 0.8195

## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5881        | 1.0   | 941  | 0.5179          | 0.7917   | 0.7915 |
| 0.4524        | 2.0   | 1882 | 0.5121          | 0.8097   | 0.8103 |
| 0.3749        | 3.0   | 2823 | 0.5268          | 0.8142   | 0.8142 |
| 0.3159        | 4.0   | 3764 | 0.5388          | 0.8176   | 0.8176 |
| 0.2721        | 5.0   | 4705 | 0.5624          | 0.8195   | 0.8195 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual", "model-index": [{"name": "xlm-roberta-base-finetuned-language-detection", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual autotrain_compatible endpoints_compatible region:us