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distilbert-base-uncased-finetuned-vk – AI Model by bruhwalkk | AlphaNeural AI
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bruhwalkk
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distilbert-base-uncased-finetuned-vk
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transformers
pytorch
tensorboard
distilbert
fill-mask
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-vk
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: 0.2150
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.3219
1.0
12032
0.2150
Framework versions
Transformers 4.27.4
Pytorch 1.13.0
Datasets 2.1.0
Tokenizers 0.13.2
