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model_output – AI Model by drkumaranu165 | AlphaNeural AI
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model_output
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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model_output
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.7401
Precision: 0.3034
Recall: 0.3889
F1: 0.2611
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: 3e-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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
No log
1.0
1
1.8269
0.3056
0.3889
0.2643
No log
2.0
2
1.7679
0.3034
0.3889
0.2611
No log
3.0
3
1.7401
0.3034
0.3889
0.2611
Framework versions
Transformers 4.54.1
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.4
