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xlm-roberta-base-finetuned-sinquad-v1 – AI Model by 9wimu9 | AlphaNeural AI
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9wimu9
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xlm-roberta-base-finetuned-sinquad-v1
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transformers
pytorch
xlm-roberta
question-answering
generated_from_trainer
mit
endpoints_compatible
us
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xlm-roberta-base-finetuned-sinquad-v1
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: 0.8768
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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
1.7867
1.0
93
1.1912
1.1577
2.0
186
0.9806
0.9607
3.0
279
0.9077
0.8221
4.0
372
0.8981
0.5837
5.0
465
0.8768
Framework versions
Transformers 4.30.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.6.1
Tokenizers 0.12.1
{'exact_match': 65.01524390243902, 'f1': 83.20167371970088}
