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my_awesome_wnut_model – AI Model by Xian-Xiang | AlphaNeural AI
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my_awesome_wnut_model
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
wnut_17
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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my_awesome_wnut_model
This model is a fine-tuned version of
distilbert-base-uncased
on the wnut_17 dataset. It achieves the following results on the evaluation set:
Loss: 0.2777
Precision: 0.4880
Recall: 0.2641
F1: 0.3428
Accuracy: 0.9395
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: 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
No log
1.0
213
0.2870
0.3758
0.2132
0.2720
0.9360
No log
2.0
426
0.2777
0.4880
0.2641
0.3428
0.9395
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2
