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ModernEMO-base-multilabel – AI Model by Jsevisal | AlphaNeural AI
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Jsevisal
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ModernEMO-base-multilabel
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transformers
safetensors
modernbert
text-classification
generated_from_trainer
Jsevisal/go_emotions_ekman
google-research-datasets/go_emotions
answerdotai/ModernBERT-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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ModernEMO-base
This model is a fine-tuned version of
answerdotai/ModernBERT-base
on
Jsevisal/go_emotions_ekman
It achieves the following results on the evaluation set:
Loss: 0.2224
F1: 0.7037
Roc Auc: 0.8143
Accuracy: 0.6226
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: 8e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Roc Auc
Accuracy
0.2162
1.0
2714
0.2049
0.6920
0.7979
0.6010
0.1553
2.0
5428
0.2224
0.7037
0.8143
0.6226
Framework versions
Transformers 4.49.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
