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udpos28-sm-all-POS – AI Model by jordyvl | AlphaNeural AI
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udpos28-sm-all-POS
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
udpos28
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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udpos28-sm-all-POS
This model is a fine-tuned version of
bert-base-cased
on the udpos28 dataset. It achieves the following results on the evaluation set:
Loss: 0.1479
Precision: 0.9587
Recall: 0.9589
F1: 0.9588
Accuracy: 0.9648
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1261
1.0
4978
0.1358
0.9513
0.9510
0.9512
0.9581
0.0788
2.0
9956
0.1326
0.9578
0.9578
0.9578
0.9642
0.0424
3.0
14934
0.1479
0.9587
0.9589
0.9588
0.9648
Framework versions
Transformers 4.18.0
Pytorch 1.10.2+cu102
Datasets 2.2.2
Tokenizers 0.12.1
