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# V3_20230929-10-xlm-roberta-base-new

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:
- Accuracy: 0.5220
- Loss: 2.6330

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.1015        | 1.82  | 200  | 0.3198   | 3.7702          |
| 3.6284        | 3.64  | 400  | 0.3944   | 3.2847          |
| 3.34          | 5.45  | 600  | 0.3976   | 3.4237          |
| 3.1657        | 7.27  | 800  | 0.4689   | 2.7734          |
| 2.9985        | 9.09  | 1000 | 0.4281   | 3.0105          |
| 2.9212        | 10.91 | 1200 | 0.4745   | 2.7150          |
| 2.7515        | 12.73 | 1400 | 0.4956   | 2.5690          |
| 2.7021        | 14.55 | 1600 | 0.4878   | 2.5398          |
| 2.681         | 16.36 | 1800 | 0.5490   | 2.3340          |
| 2.6221        | 18.18 | 2000 | 0.5189   | 2.6843          |
| 2.5678        | 20.0  | 2200 | 0.5220   | 2.6330          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "xlm-roberta-base", "model-index": [{"name": "V3_20230929-10-xlm-roberta-base-new", "results": []}]}
transformers pytorch xlm-roberta fill-mask generated_from_trainer base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us