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bert-stock-sentiment-analyzer – AI Model by Vasanth | AlphaNeural AI
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Vasanth
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bert-stock-sentiment-analyzer
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-stock-sentiment-analyzer
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4819
Accuracy: 0.8604
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: 16
eval_batch_size: 16
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
0.5818
1.0
1250
0.4290
0.8352
0.3313
2.0
2500
0.3899
0.8568
0.2029
3.0
3750
0.4819
0.8604
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
