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my_finetuned_wnut_model_1012 – AI Model by mircoboettcher | AlphaNeural AI
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mircoboettcher
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my_finetuned_wnut_model_1012
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
wnut_17
dslim/bert-base-NER
finetune
mit
model-index
autotrain_compatible
endpoints_compatible
us
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my_finetuned_wnut_model_1012
This model is a fine-tuned version of
dslim/bert-base-NER
on the wnut_17 dataset. It achieves the following results on the evaluation set:
Loss: 0.3466
Precision: 0.5545
Recall: 0.3865
F1: 0.4555
Accuracy: 0.9478
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: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
213
0.3387
0.4596
0.4004
0.4279
0.9446
No log
2.0
426
0.3275
0.5357
0.3892
0.4509
0.9476
0.0285
3.0
639
0.3466
0.5545
0.3865
0.4555
0.9478
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
