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bert-base-cnn – AI Model by harish3742 | AlphaNeural AI
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harish3742
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bert-base-cnn
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transformers
tensorboard
safetensors
encoder-decoder
text2text-generation
generated_from_trainer
endpoints_compatible
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bert-base-cnn
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3839
Rouge2 Precision: 0.0112
Rouge2 Recall: 0.0386
Rouge2 Fmeasure: 0.0162
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge2 Precision
Rouge2 Recall
Rouge2 Fmeasure
No log
1.0
8
1.6622
0.0104
0.042
0.0164
No log
2.0
16
1.3839
0.0112
0.0386
0.0162
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
