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factual-consistency-classification-ja-avgpool-unfrozen – AI Model by liwii | AlphaNeural AI
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liwii
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factual-consistency-classification-ja-avgpool-unfrozen
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transformers
pytorch
distilbert
generated_from_trainer
line-corporation/line-distilbert-base-japanese
finetune
apache-2.0
endpoints_compatible
us
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factual-consistency-classification-ja-avgpool-unfrozen
This model is a fine-tuned version of
line-corporation/line-distilbert-base-japanese
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2583
Accuracy: 0.9121
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: 0.0001
train_batch_size: 64
eval_batch_size: 8
seed: 42
distributed_type: tpu
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
306
0.2837
0.8691
0.3826
2.0
612
0.2294
0.9121
0.3826
3.0
918
0.2583
0.9121
Framework versions
Transformers 4.34.0
Pytorch 2.0.0+cu118
Datasets 2.14.5
Tokenizers 0.14.0
