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emotion_detection_model1 – AI Model by ShamraizAbid | AlphaNeural AI
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emotion_detection_model1
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transformers
safetensors
roberta
text-classification
go_emotions
emotion
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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emotion_detection_model1
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3724
Accuracy: 0.5772
F1: 0.5701
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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
1.3216
1.0
2714
1.4223
0.5702
0.5500
1.3851
2.0
5428
1.3554
0.5820
0.5742
1.0861
3.0
8142
1.3724
0.5772
0.5701
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.1
Tokenizers 0.21.1
