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distilbert-base-uncased – AI Model by bloomdata | AlphaNeural AI
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bloomdata
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distilbert-base-uncased
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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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distilbert-base-uncased
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: 0.0007
Precision: 1.0
Recall: 1.0
F1: 1.0
Accuracy: 1.0
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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0025
0.7273
500
0.0007
1.0
1.0
1.0
1.0
0.0011
1.4545
1000
0.0003
1.0
1.0
1.0
1.0
Framework versions
Transformers 4.46.0
Pytorch 2.5.1+cu124
Datasets 3.0.2
Tokenizers 0.20.1
