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my_awesome_wnut_model – AI Model by Longxiang | AlphaNeural AI
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Longxiang
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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: 0.2690
Precision: 0.5890
Recall: 0.3188
F1: 0.4137
Accuracy: 0.9423
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
0.2809
0.5670
0.2743
0.3698
0.9393
No log
2.0
426
0.2690
0.5890
0.3188
0.4137
0.9423
Framework versions
Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
