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albert-tiny-chinese-david-ner – AI Model by davidliu1110 | AlphaNeural AI
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albert-tiny-chinese-david-ner
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transformers
pytorch
albert
token-classification
generated_from_trainer
gpl-3.0
autotrain_compatible
endpoints_compatible
us
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albert-tiny-chinese-david-ner
This model is a fine-tuned version of
ckiplab/albert-tiny-chinese-ws
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3415
Precision: 0.6062
Recall: 0.6690
F1: 0.6361
Accuracy: 0.9055
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: 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
Precision
Recall
F1
Accuracy
0.1796
1.4
500
0.3368
0.6201
0.6586
0.6388
0.9046
0.1374
2.8
1000
0.3415
0.6062
0.6690
0.6361
0.9055
Framework versions
Transformers 4.29.0.dev0
Pytorch 1.10.1+cu113
Datasets 2.11.0
Tokenizers 0.13.3
