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tiny_bert_km_50_v2_wnli – AI Model by Hartunka | AlphaNeural AI
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Hartunka
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tiny_bert_km_50_v2_wnli
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transformers
tensorboard
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distilbert
text-classification
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glue
Hartunka/tiny_bert_km_50_v2
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tiny_bert_km_50_v2_wnli
This model is a fine-tuned version of
Hartunka/tiny_bert_km_50_v2
on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
Loss: 0.7216
Accuracy: 0.3944
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: 5e-05
train_batch_size: 256
eval_batch_size: 256
seed: 10
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
num_epochs: 50
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.7082
1.0
3
0.7216
0.3944
0.6925
2.0
6
0.7241
0.3662
0.6924
3.0
9
0.7375
0.3944
0.6921
4.0
12
0.7406
0.3521
0.6919
5.0
15
0.7428
0.3380
0.6904
6.0
18
0.7543
0.3239
Framework versions
Transformers 4.50.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.21.1
