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aleph_bert-finetuned-ner – AI Model by msperka | AlphaNeural AI
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msperka
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aleph_bert-finetuned-ner
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
nemo_corpus
onlplab/alephbert-base
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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aleph_bert-finetuned-ner
This model is a fine-tuned version of
onlplab/alephbert-base
on the nemo_corpus dataset. It achieves the following results on the evaluation set:
Loss: 0.1408
Precision: 0.8333
Recall: 0.8262
F1: 0.8298
Accuracy: 0.9739
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: 8
eval_batch_size: 8
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
0.042
1.0
618
0.1317
0.8198
0.8068
0.8132
0.9720
0.0185
2.0
1236
0.1367
0.8224
0.8214
0.8219
0.9714
0.0185
3.0
1854
0.1408
0.8333
0.8262
0.8298
0.9739
Framework versions
Transformers 4.35.2
Pytorch 2.0.1+cpu
Datasets 2.15.0
Tokenizers 0.15.0
