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albert-base-v2-finetuned-ner – AI Model by ankurani | AlphaNeural AI
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ankurani
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albert-base-v2-finetuned-ner
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transformers
pytorch
albert
token-classification
generated_from_trainer
plod-filtered
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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albert-base-v2-finetuned-ner
This model is a fine-tuned version of
albert-base-v2
on the plod-filtered dataset. It achieves the following results on the evaluation set:
Loss: 0.0319
Precision: 0.9890
Recall: 0.9881
F1: 0.9886
Accuracy: 0.9884
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: 1e-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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0649
1.0
3018
0.0471
0.9838
0.9814
0.9826
0.9818
0.0442
2.0
6036
0.0319
0.9890
0.9881
0.9886
0.9884
Framework versions
Transformers 4.22.2
Pytorch 1.12.1+cu113
Datasets 2.5.1
Tokenizers 0.12.1
