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# V3_20230929-5-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: 0.5172
- Loss: 2.6032

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.4963        | 0.46  | 200  | 0.2938   | nan             |
| 4.0957        | 0.91  | 400  | 0.3098   | 3.5806          |
| 3.7431        | 1.37  | 600  | 0.3455   | nan             |
| 3.6542        | 1.82  | 800  | 0.3075   | nan             |
| 3.5585        | 2.28  | 1000 | 0.3546   | 3.4012          |
| 3.4027        | 2.73  | 1200 | 0.4049   | 3.2653          |
| 3.3416        | 3.19  | 1400 | 0.4053   | nan             |
| 3.314         | 3.64  | 1600 | 0.4505   | nan             |
| 3.2035        | 4.1   | 1800 | 0.4140   | 2.8518          |
| 3.1372        | 4.56  | 2000 | 0.4553   | 2.7572          |
| 3.0738        | 5.01  | 2200 | 0.4188   | 3.1020          |
| 3.0354        | 5.47  | 2400 | 0.4483   | 2.9353          |
| 3.0447        | 5.92  | 2600 | 0.4729   | 2.8608          |
| 2.6643        | 6.38  | 2800 | 0.4833   | 2.6200          |
| 2.8909        | 6.83  | 3000 | 0.4858   | 2.4677          |
| 2.9888        | 7.29  | 3200 | 0.4676   | 2.8088          |
| 2.8658        | 7.74  | 3400 | 0.5162   | 2.6409          |
| 2.7865        | 8.2   | 3600 | 0.5294   | nan             |
| 2.8237        | 8.66  | 3800 | 0.4986   | nan             |
| 2.7182        | 9.11  | 4000 | 0.5087   | nan             |
| 2.7962        | 9.57  | 4200 | 0.5459   | nan             |
| 2.5706        | 10.02 | 4400 | 0.4801   | nan             |
| 2.528         | 10.48 | 4600 | 0.4893   | 2.2799          |
| 2.7482        | 10.93 | 4800 | 0.5227   | nan             |
| 2.799         | 11.39 | 5000 | 0.4501   | nan             |
| 2.471         | 11.85 | 5200 | 0.5323   | 2.4217          |
| 2.6071        | 12.3  | 5400 | 0.5420   | nan             |
| 2.5139        | 12.76 | 5600 | 0.5511   | 2.1409          |
| 2.4214        | 13.21 | 5800 | 0.5215   | 2.4055          |
| 2.608         | 13.67 | 6000 | 0.5197   | 2.3034          |
| 2.5468        | 14.12 | 6200 | 0.5259   | nan             |
| 2.4802        | 14.58 | 6400 | 0.5172   | 2.6032          |


### 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_20230929-5-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