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xlm-r-qa-small-squad – AI Model by mrizalf7 | AlphaNeural AI
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mrizalf7
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xlm-r-qa-small-squad
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transformers
pytorch
tensorboard
xlm-roberta
question-answering
generated_from_trainer
mit
endpoints_compatible
us
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xlm-r-qa-small-squad
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: 1.9800
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: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.2394
1.0
5437
1.9701
0.9683
2.0
10874
1.9800
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
