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roberta-base-bne-finetuned-sqac – AI Model by nlp-en-es | AlphaNeural AI
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roberta-base-bne-finetuned-sqac
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transformers
pytorch
safetensors
roberta
question-answering
generated_from_trainer
es
sqac
BSC-LT/roberta-base-bne
finetune
apache-2.0
model-index
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: 1.2111
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
0.9971
1.0
1196
0.8646
0.482
2.0
2392
0.9334
0.1652
3.0
3588
1.2111
Framework versions
Transformers 4.11.2
Pytorch 1.9.0+cu111
Datasets 1.12.1
Tokenizers 0.10.3
