bert_finetuned – AI Model by amar9023 | AlphaNeural AI

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amar9023/
bert_finetuned

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

text-embeddings-inference

endpoints_compatible

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bert_finetuned

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: 0.5511
Accuracy: 0.95
F1: 0.9499

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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6858	1.0	10	0.6073	0.8	0.7917
0.6017	2.0	20	0.5511	0.95	0.9499

Framework versions

Transformers 4.49.0
Pytorch 2.12.0
Datasets 2.12.0
Tokenizers 0.21.0