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# V3_20230929-4-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: 0.4828
- Loss: 2.7092

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.6198        | 0.46  | 200  | 0.35     | nan             |
| 4.1243        | 0.91  | 400  | 0.3244   | nan             |
| 3.7837        | 1.37  | 600  | 0.3273   | nan             |
| 3.7335        | 1.82  | 800  | 0.3293   | nan             |
| 3.4681        | 2.28  | 1000 | 0.3963   | nan             |
| 3.4469        | 2.73  | 1200 | 0.4186   | nan             |
| 3.3005        | 3.19  | 1400 | 0.4307   | 3.0076          |
| 3.2722        | 3.64  | 1600 | 0.4257   | nan             |
| 3.3514        | 4.1   | 1800 | 0.4832   | 2.5834          |
| 3.0384        | 4.56  | 2000 | 0.4397   | 2.9867          |
| 3.0971        | 5.01  | 2200 | 0.3799   | nan             |
| 2.903         | 5.47  | 2400 | 0.5107   | 2.6798          |
| 3.006         | 5.92  | 2600 | 0.4504   | 2.9205          |
| 2.7999        | 6.38  | 2800 | 0.4809   | nan             |
| 2.8268        | 6.83  | 3000 | 0.4321   | 2.5767          |
| 2.8814        | 7.29  | 3200 | 0.4706   | 2.7337          |
| 2.6975        | 7.74  | 3400 | 0.4831   | nan             |
| 2.7642        | 8.2   | 3600 | 0.4669   | 2.8202          |
| 2.8996        | 8.66  | 3800 | 0.5187   | 2.7733          |
| 2.6657        | 9.11  | 4000 | 0.4697   | nan             |
| 2.7318        | 9.57  | 4200 | 0.4532   | nan             |
| 2.7065        | 10.02 | 4400 | 0.4785   | 2.5715          |
| 2.5635        | 10.48 | 4600 | 0.4969   | 2.8287          |
| 2.5543        | 10.93 | 4800 | 0.4909   | 2.3697          |
| 2.5284        | 11.39 | 5000 | 0.4706   | nan             |
| 2.5401        | 11.85 | 5200 | 0.4679   | nan             |
| 2.4722        | 12.3  | 5400 | 0.4983   | 2.3692          |
| 2.5367        | 12.76 | 5600 | 0.5663   | nan             |
| 2.5331        | 13.21 | 5800 | 0.525    | nan             |
| 2.183         | 13.67 | 6000 | 0.5137   | 2.3417          |
| 2.4319        | 14.12 | 6200 | 0.5409   | 2.2783          |
| 2.4168        | 14.58 | 6400 | 0.4828   | 2.7092          |


### 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_20230929-4-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