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bert-emotion – AI Model by zhangpn | AlphaNeural AI
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zhangpn
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bert-emotion
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transformers
pytorch
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-emotion
This model is a fine-tuned version of
distilbert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.0958
Precision: 0.7192
Recall: 0.7219
Fscore: 0.7200
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: 4
eval_batch_size: 4
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
Precision
Recall
Fscore
0.8487
1.0
815
0.9013
0.6936
0.6375
0.6462
0.5456
2.0
1630
0.9633
0.7383
0.7153
0.7253
0.2589
3.0
2445
1.0958
0.7192
0.7219
0.7200
Framework versions
Transformers 4.51.1
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
