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multilabel_mood_distilbert – AI Model by Sairii | AlphaNeural AI
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Sairii
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multilabel_mood_distilbert
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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multilabel_mood_distilbert
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0852
F1: 0.5646
Precision: 0.7199
Recall: 0.4644
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: 2e-05
train_batch_size: 32
eval_batch_size: 32
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
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Precision
Recall
0.138
1.0
1357
0.0932
0.5104
0.7194
0.3955
0.0888
2.0
2714
0.0860
0.5498
0.7359
0.4389
0.0807
3.0
4071
0.0852
0.5646
0.7199
0.4644
Framework versions
Transformers 4.53.2
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.2
