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ner-railway – AI Model by linhdzqua148 | AlphaNeural AI
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linhdzqua148
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ner-railway
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transformers
safetensors
bert
token-classification
generated_from_trainer
knosing/japanese_ner_model
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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ner-railway
This model is a fine-tuned version of
knosing/japanese_ner_model
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0072
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: 32
eval_batch_size: 32
seed: 42
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.0093
1.0
1605
0.0082
0.0067
2.0
3210
0.0078
0.0052
3.0
4815
0.0072
Framework versions
Transformers 4.52.3
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1
