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gigazine-labeling – AI Model by tuna2134 | AlphaNeural AI
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tuna2134
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gigazine-labeling
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safetensors
bert
generated_from_trainer
tohoku-nlp/bert-base-japanese-v3
finetune
apache-2.0
us
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gigazine-labeling
This model is a fine-tuned version of
tohoku-nlp/bert-base-japanese-v3
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3062
Accuracy: 0.623
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.4089
1.0
125
1.5892
0.551
1.2661
2.0
250
1.3291
0.601
0.6811
3.0
375
1.3062
0.623
Framework versions
Transformers 4.43.4
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
