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# my_awesome_model

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0506
- Accuracy: 0.6959

## 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: 8e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 383  | 1.6014          | 0.3719   |
| 1.6917        | 2.0   | 766  | 1.1865          | 0.5951   |
| 1.1046        | 3.0   | 1149 | 1.0636          | 0.6473   |
| 0.9029        | 4.0   | 1532 | 1.0561          | 0.6603   |
| 0.9029        | 5.0   | 1915 | 1.0121          | 0.6794   |
| 0.765         | 6.0   | 2298 | 0.9676          | 0.7072   |
| 0.6696        | 7.0   | 2681 | 0.9890          | 0.6985   |
| 0.5756        | 8.0   | 3064 | 1.0216          | 0.7107   |
| 0.5756        | 9.0   | 3447 | 1.0752          | 0.6881   |
| 0.5302        | 10.0  | 3830 | 1.0506          | 0.6959   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "xlm-roberta-base", "model-index": [{"name": "my_awesome_model", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us