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230615_wnut_model – AI Model by Sogangina | AlphaNeural AI
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230615_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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230615_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: 0.2816
Precision: 0.5185
Recall: 0.2734
F1: 0.3580
Accuracy: 0.9398
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
0.2876
0.3942
0.2141
0.2775
0.9363
No log
2.0
426
0.2816
0.5185
0.2734
0.3580
0.9398
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.0
Tokenizers 0.13.3
