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# V3_20230929-7-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: 0.5365
- Loss: 2.4888

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.1508        | 1.82  | 200  | 0.375    | 3.5633          |
| 3.6085        | 3.64  | 400  | 0.4119   | 3.1221          |
| 3.3578        | 5.45  | 600  | 0.4551   | 3.0793          |
| 3.1507        | 7.27  | 800  | 0.4429   | 2.9413          |
| 3.0346        | 9.09  | 1000 | 0.4583   | 2.8397          |
| 2.895         | 10.91 | 1200 | 0.4667   | 2.6774          |
| 2.755         | 12.73 | 1400 | 0.5144   | 2.6758          |
| 2.732         | 14.55 | 1600 | 0.4986   | 2.3828          |
| 2.6781        | 16.36 | 1800 | 0.5072   | 2.6525          |
| 2.6185        | 18.18 | 2000 | 0.5183   | 2.6757          |
| 2.6455        | 20.0  | 2200 | 0.5365   | 2.4888          |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "xlm-roberta-base", "model-index": [{"name": "V3_20230929-7-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