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ug_pos_tagger – AI Model by onkej | AlphaNeural AI
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onkej
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ug_pos_tagger
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-multilingual-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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ug_pos_tagger
This model is a fine-tuned version of
bert-base-multilingual-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.8548
Accuracy: 0.7457
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.0582
1.0
83
0.9918
0.6856
0.9264
2.0
166
0.8798
0.7285
0.853
3.0
249
0.8548
0.7457
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
