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testThesisSmallSMP – AI Model by Nonzerophilip | AlphaNeural AI
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Nonzerophilip
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testThesisSmallSMP
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transformers
pytorch
bert
token-classification
generated_from_trainer
KBLab/bert-base-swedish-cased-ner
finetune
autotrain_compatible
endpoints_compatible
us
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testThesisSmallSMP
This model is a fine-tuned version of
KBLab/bert-base-swedish-cased-ner
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3275
Precision: 0.6826
Recall: 0.6477
F1: 0.6647
Accuracy: 0.8940
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
No log
1.0
39
0.4518
0.4107
0.2614
0.3194
0.8555
No log
2.0
78
0.3469
0.6687
0.6193
0.6431
0.8923
No log
3.0
117
0.3275
0.6826
0.6477
0.6647
0.8940
Framework versions
Transformers 4.33.0
Pytorch 2.0.1
Datasets 2.14.5
Tokenizers 0.13.3
