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bert-sentiment-analysis – AI Model by muralik0115 | AlphaNeural AI
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muralik0115
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bert-sentiment-analysis
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transformers
safetensors
bert
text-classification
generated_from_trainer
emotion
google-bert/bert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-sentiment-analysis
This model is a fine-tuned version of
google-bert/bert-base-uncased
on the emotion dataset. It achieves the following results on the evaluation set:
Loss: 0.1285
Accuracy: 0.946
F1: 0.9458
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: 24
eval_batch_size: 24
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
F1
0.4104
1.0
667
0.1901
0.93
0.9306
0.1271
2.0
1334
0.1207
0.94
0.9391
0.0832
3.0
2001
0.1285
0.946
0.9458
Framework versions
Transformers 4.40.1
Pytorch 2.3.0
Datasets 2.19.0
Tokenizers 0.19.1
