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# V3_20230929-6-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: 0.5780
- Loss: 2.1766

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.4638        | 0.46  | 200  | 0.2889   | nan             |
| 4.1893        | 0.91  | 400  | 0.3536   | nan             |
| 3.9393        | 1.37  | 600  | 0.3672   | nan             |
| 3.6824        | 1.82  | 800  | 0.3609   | nan             |
| 3.5332        | 2.28  | 1000 | 0.4353   | nan             |
| 3.5164        | 2.73  | 1200 | 0.4039   | 3.3258          |
| 3.3856        | 3.19  | 1400 | 0.4489   | 2.4897          |
| 3.454         | 3.64  | 1600 | 0.4209   | 3.2397          |
| 3.2161        | 4.1   | 1800 | 0.4620   | 2.7198          |
| 3.175         | 4.56  | 2000 | 0.4476   | nan             |
| 3.1915        | 5.01  | 2200 | 0.4670   | 2.6543          |
| 2.8989        | 5.47  | 2400 | 0.4640   | 2.8110          |
| 2.8575        | 5.92  | 2600 | 0.4848   | nan             |
| 2.9779        | 6.38  | 2800 | 0.4438   | nan             |
| 2.9945        | 6.83  | 3000 | 0.4869   | 2.5596          |
| 2.8321        | 7.29  | 3200 | 0.4474   | 2.5483          |
| 2.7283        | 7.74  | 3400 | 0.4553   | 2.9584          |
| 2.7695        | 8.2   | 3600 | 0.4645   | 2.3643          |
| 2.9078        | 8.66  | 3800 | 0.5055   | nan             |
| 2.6554        | 9.11  | 4000 | 0.5202   | 2.3099          |
| 2.6683        | 9.57  | 4200 | 0.4558   | nan             |
| 2.7513        | 10.02 | 4400 | 0.5183   | 2.5005          |
| 2.7285        | 10.48 | 4600 | 0.5042   | nan             |
| 2.5985        | 10.93 | 4800 | 0.5432   | 2.4976          |
| 2.5506        | 11.39 | 5000 | 0.5073   | nan             |
| 2.5256        | 11.85 | 5200 | 0.5095   | 2.4731          |
| 2.4992        | 12.3  | 5400 | 0.5710   | nan             |
| 2.5342        | 12.76 | 5600 | 0.5644   | nan             |
| 2.7334        | 13.21 | 5800 | 0.5241   | 2.2573          |
| 2.6112        | 13.67 | 6000 | 0.5714   | 1.9512          |
| 2.3563        | 14.12 | 6200 | 0.5301   | nan             |
| 2.4953        | 14.58 | 6400 | 0.5780   | 2.1766          |


### 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_20230929-6-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