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bert-xnli-de-classifier – AI Model by gayanin | AlphaNeural AI
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gayanin
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bert-xnli-de-classifier
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transformers
pytorch
bert
text-classification
generated_from_trainer
xnli
mit
model-index
autotrain_compatible
endpoints_compatible
us
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bert-xnli-de-classifier
This model is a fine-tuned version of
bert-base-german-cased
on the xnli dataset. It achieves the following results on the evaluation set:
Loss: 0.5897
Accuracy: 0.7807
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.554
1.0
6136
0.5783
0.7675
0.4946
2.0
12272
0.5471
0.7892
0.3416
3.0
18408
0.5897
0.7807
Framework versions
Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
