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# V3_20230929-3-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: 0.5509
- Loss: 2.1676

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.4138        | 0.46  | 200  | 0.2723   | nan             |
| 4.0972        | 0.91  | 400  | 0.3135   | nan             |
| 3.7299        | 1.37  | 600  | 0.3289   | nan             |
| 3.7476        | 1.82  | 800  | 0.3242   | 3.6812          |
| 3.8098        | 2.28  | 1000 | 0.4011   | 3.5966          |
| 3.6111        | 2.73  | 1200 | 0.4      | 2.8744          |
| 3.3202        | 3.19  | 1400 | 0.4334   | 2.9269          |
| 3.3557        | 3.64  | 1600 | 0.3649   | nan             |
| 3.198         | 4.1   | 1800 | 0.4349   | nan             |
| 3.1623        | 4.56  | 2000 | 0.4237   | 2.9731          |
| 3.1379        | 5.01  | 2200 | 0.4521   | nan             |
| 3.0795        | 5.47  | 2400 | 0.4538   | 2.8971          |
| 3.0176        | 5.92  | 2600 | 0.4138   | 3.0068          |
| 2.9956        | 6.38  | 2800 | 0.4729   | nan             |
| 2.9666        | 6.83  | 3000 | 0.4674   | 2.3240          |
| 2.9124        | 7.29  | 3200 | 0.5039   | nan             |
| 2.9806        | 7.74  | 3400 | 0.4457   | nan             |
| 2.7471        | 8.2   | 3600 | 0.5138   | 2.4373          |
| 2.7762        | 8.66  | 3800 | 0.4963   | 2.4425          |
| 2.7485        | 9.11  | 4000 | 0.5302   | nan             |
| 2.6488        | 9.57  | 4200 | 0.5499   | 2.3581          |
| 2.69          | 10.02 | 4400 | 0.5066   | 2.3862          |
| 2.6669        | 10.48 | 4600 | 0.4802   | 2.4588          |
| 2.5595        | 10.93 | 4800 | 0.4938   | 2.4186          |
| 2.5512        | 11.39 | 5000 | 0.5076   | 2.5922          |
| 2.5686        | 11.85 | 5200 | 0.5648   | nan             |
| 2.5772        | 12.3  | 5400 | 0.5480   | 2.4634          |
| 2.5701        | 12.76 | 5600 | 0.5497   | 2.5381          |
| 2.3937        | 13.21 | 5800 | 0.5310   | nan             |
| 2.5274        | 13.67 | 6000 | 0.5681   | nan             |
| 2.3513        | 14.12 | 6200 | 0.5671   | nan             |
| 2.529         | 14.58 | 6400 | 0.5509   | 2.1676          |


### 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_20230929-3-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