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roberta-base-bne-finetuned-sqac – AI Model by jamanca94 | AlphaNeural AI
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jamanca94
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roberta-base-bne-finetuned-sqac
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transformers
pytorch
tensorboard
roberta
question-answering
generated_from_trainer
sqac
apache-2.0
endpoints_compatible
us
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roberta-base-bne-finetuned-sqac
This model is a fine-tuned version of
BSC-TeMU/roberta-base-bne
on the sqac dataset. It achieves the following results on the evaluation set:
Loss: 1.1472
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.9881
1.0
1196
0.8653
0.4671
2.0
2392
0.9053
0.1506
3.0
3588
1.1472
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
