bert-base-uncased-finetuned-cda – AI Model by zz990906 | AlphaNeural AI

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zz990906/
bert-base-uncased-finetuned-cda

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google-bert/bert-base-uncased

autotrain_compatible

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bert-base-uncased-finetuned-cda

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: 1.6567

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.0518	1.0	391	1.8074
1.8971	2.0	782	1.7770
1.8422	3.0	1173	1.7504
1.7984	4.0	1564	1.7272
1.777	5.0	1955	1.6912
1.7532	6.0	2346	1.6920
1.7323	7.0	2737	1.6826
1.7251	8.0	3128	1.6687
1.7108	9.0	3519	1.6553
1.7076	10.0	3910	1.6702

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1