
# twitter-emotion-deberta-v3-base

This model is a fine-tuned version of [DeBERTa-v3](https://huggingface.co/microsoft/deberta-v3-base). It achieves the following results on the evaluation set:
- Loss: 0.1474
- Accuracy: 0.937

### 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 deberta-v2 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 #deberta-v2 #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 


# twitter-emotion-deberta-v3-base

This model is a fine-tuned version of DeBERTa-v3. It achieves the following results on the evaluation set:
- Loss: 0.1474
- Accuracy: 0.937

### 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
# twitter-emotion-deberta-v3-base

This model is a fine-tuned version of DeBERTa-v3. It achieves the following results on the evaluation set:
- Loss: 0.1474
- Accuracy: 0.937 ### 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 #deberta-v2 #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # twitter-emotion-deberta-v3-base

This model is a fine-tuned version of DeBERTa-v3. It achieves the following results on the evaluation set:
- Loss: 0.1474
- Accuracy: 0.937 ### 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 #deberta-v2 #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
# twitter-emotion-deberta-v3-base

This model is a fine-tuned version of DeBERTa-v3. It achieves the following results on the evaluation set:
- Loss: 0.1474
- Accuracy: 0.937### 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