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test-ner – AI Model by Falah | AlphaNeural AI
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Falah
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test-ner
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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test-ner
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0585
Precision: 0.8389
Recall: 0.8739
F1: 0.8560
Accuracy: 0.9857
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: 0.0001
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
229
0.0617
0.7850
0.8498
0.8161
0.9813
No log
2.0
458
0.0542
0.8191
0.8693
0.8435
0.9839
0.0618
3.0
687
0.0585
0.8389
0.8739
0.8560
0.9857
Framework versions
Transformers 4.27.1
Pytorch 2.0.1+cu118
Datasets 2.9.0
Tokenizers 0.13.3
