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bert-base-uncased-classification-seq2seq – AI Model by irfanamal | AlphaNeural AI
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irfanamal
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bert-base-uncased-classification-seq2seq
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transformers
pytorch
encoder-decoder
text2text-generation
generated_from_trainer
endpoints_compatible
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bert-base-uncased-classification-seq2seq
This model is a fine-tuned version of
on the None dataset. It achieves the following results on the evaluation set:
Loss: 14.625
Accuracy: 0.1667
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0056
1.0
2500
12.4694
0.1667
0.0015
2.0
5000
13.2865
0.1667
0.0006
3.0
7500
13.8803
0.1667
0.0003
4.0
10000
14.3258
0.1667
0.0002
5.0
12500
14.625
0.1667
Framework versions
Transformers 4.29.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3
