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bert_base_km_20_v1_sst2 – AI Model by Hartunka | AlphaNeural AI
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Hartunka
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bert_base_km_20_v1_sst2
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transformers
tensorboard
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distilbert
text-classification
generated_from_trainer
en
glue
Hartunka/bert_base_km_20_v1
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autotrain_compatible
endpoints_compatible
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bert_base_km_20_v1_sst2
This model is a fine-tuned version of
Hartunka/bert_base_km_20_v1
on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
Loss: 0.4363
Accuracy: 0.8085
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
0.4071
1.0
264
0.4363
0.8085
0.2234
2.0
528
0.5352
0.8028
0.1578
3.0
792
0.7096
0.7982
0.1145
4.0
1056
0.5919
0.7982
0.0841
5.0
1320
0.7548
0.7833
0.0635
6.0
1584
0.9019
0.7798
Framework versions
Transformers 4.50.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.21.1
