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my_awesome_wnut_model2 – AI Model by gonzalezrostani | AlphaNeural AI
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my_awesome_wnut_model2
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transformers
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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my_awesome_wnut_model2
This model is a fine-tuned version of
distilbert/distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
eval_loss: 0.1068
eval_precision: 0.55
eval_recall: 0.3587
eval_f1: 0.4342
eval_accuracy: 0.9605
eval_runtime: 4.4133
eval_samples_per_second: 35.574
eval_steps_per_second: 2.266
epoch: 2.0
step: 92
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
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cpu
Datasets 2.18.0
Tokenizers 0.15.2
