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# six-emotion-finetuned-twitter-xlm-roberta-base

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2485
- Accuracy: 0.918
- F1: 0.9186

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results



### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "six-emotion-finetuned-twitter-xlm-roberta-base", "results": []}]}
transformers pytorch tensorboard xlm-roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# six-emotion-finetuned-twitter-xlm-roberta-base

This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2485
- Accuracy: 0.918
- F1: 0.9186

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results



### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

# six-emotion-finetuned-twitter-xlm-roberta-base

This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2485
- Accuracy: 0.918
- F1: 0.9186 ## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2 ### Training results ### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # six-emotion-finetuned-twitter-xlm-roberta-base

This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2485
- Accuracy: 0.918
- F1: 0.9186 ## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2 ### Training results ### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2