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multilingual_tokenized – AI Model by Erfan2001 | AlphaNeural AI
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Erfan2001
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multilingual_tokenized
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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This model is a fine-tuned version of
bert-base-multilingual-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5995
Accuracy: 0.8444
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.665
1.0
1494
0.6023
0.8057
0.4858
2.0
2988
0.5160
0.8318
0.376
3.0
4482
0.5376
0.8353
0.2863
4.0
5976
0.5591
0.8417
0.2037
5.0
7470
0.5995
0.8444
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
