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xlm-roberta-base-finetuned-viquad – AI Model by Khanh | AlphaNeural AI
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Khanh
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xlm-roberta-base-finetuned-viquad
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transformers
pytorch
tensorboard
xlm-roberta
question-answering
generated_from_trainer
mit
endpoints_compatible
us
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xlm-roberta-base-finetuned-viquad
This model is a fine-tuned version of
xlm-roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.3761
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
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
259
2.9945
3.3665
2.0
518
2.3761
Framework versions
Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.17.0
Tokenizers 0.10.3
