
# bertweet-emotion-base

This model is a fine-tuned version of [Bertweet](https://huggingface.co/vinai/bertweet-base). It achieves the following results on the evaluation set:
- Loss: 0.1172
- Accuracy: 0.945

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 80
- eval_batch_size: 80
- lr_scheduler_type: linear
- num_epochs: 6.0 

### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3
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transformers pytorch tensorboard roberta text-classification generated_from_trainer dataset:emotion license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 


# bertweet-emotion-base

This model is a fine-tuned version of Bertweet. It achieves the following results on the evaluation set:
- Loss: 0.1172
- Accuracy: 0.945

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 80
- eval_batch_size: 80
- lr_scheduler_type: linear
- num_epochs: 6.0 

### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3
# bertweet-emotion-base

This model is a fine-tuned version of Bertweet. It achieves the following results on the evaluation set:
- Loss: 0.1172
- Accuracy: 0.945 ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 80
- eval_batch_size: 80
- lr_scheduler_type: linear
- num_epochs: 6.0 ### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # bertweet-emotion-base

This model is a fine-tuned version of Bertweet. It achieves the following results on the evaluation set:
- Loss: 0.1172
- Accuracy: 0.945 ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 80
- eval_batch_size: 80
- lr_scheduler_type: linear
- num_epochs: 6.0 ### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
# bertweet-emotion-base

This model is a fine-tuned version of Bertweet. It achieves the following results on the evaluation set:
- Loss: 0.1172
- Accuracy: 0.945### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 80
- eval_batch_size: 80
- lr_scheduler_type: linear
- num_epochs: 6.0### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3