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my_awesome_wnut_model – AI Model by hesamheidari | AlphaNeural AI
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my_awesome_wnut_model
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
wnut_17
distilbert/distilbert-base-uncased
finetune
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: 0.2763
Precision: 0.5734
Recall: 0.3040
F1: 0.3973
Accuracy: 0.9407
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 OptimizerNames.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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
213
0.2796
0.6170
0.2493
0.3551
0.9390
No log
2.0
426
0.2763
0.5734
0.3040
0.3973
0.9407
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
