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# xlm-roberta-base-finetuned-emotion

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1727
- Accuracy: 0.929
- F1: 0.9300

## 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: 32
- eval_batch_size: 32
- seed: 254
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9321        | 1.0   | 500  | 0.3098          | 0.895    | 0.8961 |
| 0.2468        | 2.0   | 1000 | 0.1798          | 0.932    | 0.9326 |
| 0.1506        | 3.0   | 1500 | 0.1727          | 0.929    | 0.9300 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "xlm-roberta-base-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion", "config": "split", "split": "validation", "args": "split"}, "metrics": [{"type": "accuracy", "value": 0.929, "name": "Accuracy"}, {"type": "f1", "value": 0.9300165528214905, "name": "F1"}]}]}]}
transformers safetensors xlm-roberta text-classification generated_from_trainer dataset:emotion base_model:xlm-roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us