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SentimentExam – AI Model by LordOfSilence | AlphaNeural AI
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LordOfSilence
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SentimentExam
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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trainer_output
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: 0.7147
Model Preparation Time: 0.0035
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: 8
eval_batch_size: 8
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Model Preparation Time
No log
1.0
3
0.7089
0.0035
No log
2.0
6
0.7145
0.0035
No log
3.0
9
0.7153
0.0035
No log
4.0
12
0.7136
0.0035
No log
5.0
15
0.7147
0.0035
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
