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roberta-emotion – AI Model by mudogruer | AlphaNeural AI
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mudogruer
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roberta-emotion
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transformers
safetensors
roberta
text-classification
generated_from_trainer
emotion
FacebookAI/roberta-base
finetune
mit
model-index
autotrain_compatible
endpoints_compatible
us
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roberta-emotion
This model is a fine-tuned version of
roberta-base
on the emotion dataset. It achieves the following results on the evaluation set:
Loss: 0.1394
Accuracy: 0.938
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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
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
0.6103
1.0
500
0.2516
0.9195
0.1981
2.0
1000
0.1747
0.9345
0.1214
3.0
1500
0.1394
0.938
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
