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# V3_20230929-2-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: 0.5469
- Loss: nan

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.4076        | 0.46  | 200  | 0.2641   | nan             |
| 4.0232        | 0.91  | 400  | 0.3172   | nan             |
| 3.9061        | 1.37  | 600  | 0.3025   | nan             |
| 3.6669        | 1.82  | 800  | 0.3241   | 3.5105          |
| 3.5761        | 2.28  | 1000 | 0.3492   | 3.2617          |
| 3.4949        | 2.73  | 1200 | 0.3894   | nan             |
| 3.3705        | 3.19  | 1400 | 0.4269   | nan             |
| 3.3901        | 3.64  | 1600 | 0.4191   | 3.3508          |
| 3.1971        | 4.1   | 1800 | 0.3889   | nan             |
| 3.1646        | 4.56  | 2000 | 0.4204   | 3.3370          |
| 2.9748        | 5.01  | 2200 | 0.4468   | 2.8025          |
| 3.0047        | 5.47  | 2400 | 0.4327   | 3.0098          |
| 2.9395        | 5.92  | 2600 | 0.4673   | 2.7967          |
| 2.8467        | 6.38  | 2800 | 0.4675   | nan             |
| 2.7492        | 6.83  | 3000 | 0.4613   | 2.8956          |
| 2.802         | 7.29  | 3200 | 0.4766   | 2.5544          |
| 2.8111        | 7.74  | 3400 | 0.4925   | nan             |
| 2.6549        | 8.2   | 3600 | 0.5013   | nan             |
| 2.7367        | 8.66  | 3800 | 0.4842   | 2.7689          |
| 2.6375        | 9.11  | 4000 | 0.5303   | nan             |
| 2.616         | 9.57  | 4200 | 0.5157   | 2.6867          |
| 2.711         | 10.02 | 4400 | 0.5357   | 2.2537          |
| 2.4239        | 10.48 | 4600 | 0.4976   | nan             |
| 2.7012        | 10.93 | 4800 | 0.5105   | 2.4325          |
| 2.5152        | 11.39 | 5000 | 0.5372   | nan             |
| 2.5798        | 11.85 | 5200 | 0.5320   | nan             |
| 2.4845        | 12.3  | 5400 | 0.5553   | nan             |
| 2.4842        | 12.76 | 5600 | 0.5206   | nan             |
| 2.4412        | 13.21 | 5800 | 0.5398   | 2.3403          |
| 2.4967        | 13.67 | 6000 | 0.5285   | 2.2010          |
| 2.4451        | 14.12 | 6200 | 0.4803   | 2.5469          |
| 2.485         | 14.58 | 6400 | 0.5469   | nan             |


### 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_20230929-2-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