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distilbert-base-uncased-finetuned-NSD – AI Model by jcardonaruiz | AlphaNeural AI
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jcardonaruiz
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distilbert-base-uncased-finetuned-NSD
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-NSD
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4041
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.8041
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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
62
0.4041
0.0
0.0
0.0
0.8041
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cpu
Datasets 2.20.0
Tokenizers 0.20.3
