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bert-base-uncased-finetuned-squad-frozen-v2 – AI Model by ericRosello | AlphaNeural AI
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ericRosello
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bert-base-uncased-finetuned-squad-frozen-v2
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
squad
apache-2.0
endpoints_compatible
us
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bert-base-uncased-finetuned-squad
This model is a fine-tuned version of
bert-base-uncased
on the squad dataset. It achieves the following results on the evaluation set:
Loss: 1.4571
Model description
Most base model weights were frozen leaving only to finetune the last layer (qa outputs) and 3 last layers of the encoder.
Training and evaluation data
Achieved EM: 76.77388836329234, F1: 85.41893520501723
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
1.2944
1.0
44262
1.3432
1.0152
2.0
88524
1.3450
1.0062
3.0
132786
1.4571
Framework versions
Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.17.0
Tokenizers 0.10.3
