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bert-base-historic-multilingual-64k-td-cased-squad-fr – AI Model by Nadav | AlphaNeural AI
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Nadav
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bert-base-historic-multilingual-64k-td-cased-squad-fr
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
mit
endpoints_compatible
us
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bert-base-historic-multilingual-64k-td-cased-squad-fr
This model is a fine-tuned version of
dbmdz/bert-base-historic-multilingual-64k-td-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.7419
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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.2
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
1.9834
1.0
3569
1.8605
1.663
2.0
7138
1.7419
Framework versions
Transformers 4.24.0
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2
