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# V3_20230929-1-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: 0.5884
- 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.5743        | 0.46  | 200  | 0.3185   | 3.6252          |
| 4.0617        | 0.91  | 400  | 0.3300   | 3.5165          |
| 3.7835        | 1.37  | 600  | 0.3238   | nan             |
| 3.7415        | 1.82  | 800  | 0.3733   | nan             |
| 3.6084        | 2.28  | 1000 | 0.3711   | 3.4266          |
| 3.5224        | 2.73  | 1200 | 0.3966   | nan             |
| 3.4781        | 3.19  | 1400 | 0.4110   | 3.0491          |
| 3.2402        | 3.64  | 1600 | 0.4381   | 3.3243          |
| 3.1612        | 4.1   | 1800 | 0.4764   | nan             |
| 3.0672        | 4.56  | 2000 | 0.4293   | 2.6114          |
| 3.0975        | 5.01  | 2200 | 0.4415   | nan             |
| 3.0579        | 5.47  | 2400 | 0.4760   | 2.6061          |
| 3.0349        | 5.92  | 2600 | 0.5012   | 2.6430          |
| 2.9009        | 6.38  | 2800 | 0.5101   | 2.6843          |
| 3.0346        | 6.83  | 3000 | 0.4803   | 2.7765          |
| 2.7554        | 7.29  | 3200 | 0.4866   | nan             |
| 2.6926        | 7.74  | 3400 | 0.5105   | 2.8698          |
| 2.8284        | 8.2   | 3600 | 0.5038   | 2.5535          |
| 2.8385        | 8.66  | 3800 | 0.5465   | 2.5647          |
| 2.731         | 9.11  | 4000 | 0.5355   | nan             |
| 2.6252        | 9.57  | 4200 | 0.5062   | 2.7420          |
| 2.5493        | 10.02 | 4400 | 0.5570   | 2.4540          |
| 2.649         | 10.48 | 4600 | 0.5495   | 2.4343          |
| 2.6669        | 10.93 | 4800 | 0.5365   | 2.2657          |
| 2.4549        | 11.39 | 5000 | 0.5508   | 2.4005          |
| 2.5627        | 11.85 | 5200 | 0.6057   | nan             |
| 2.5328        | 12.3  | 5400 | 0.5943   | 2.0599          |
| 2.6162        | 12.76 | 5600 | 0.5167   | nan             |
| 2.5906        | 13.21 | 5800 | 0.5518   | 2.1281          |
| 2.542         | 13.67 | 6000 | 0.5847   | nan             |
| 2.4217        | 14.12 | 6200 | 0.5498   | nan             |
| 2.4402        | 14.58 | 6400 | 0.5884   | 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_20230929-1-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