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albert_chinese_base-text-classification – AI Model by CeroShrijver | AlphaNeural AI
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CeroShrijver
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albert_chinese_base-text-classification
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transformers
pytorch
albert
text-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
us
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albert_chinese_base-text-classification
This model is a fine-tuned version of
voidful/albert_chinese_base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5075
Accuracy: 0.8017
Test Accuracy: 0.8393
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: 16
eval_batch_size: 16
seed: 42
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
0.4953
1.0
1009
0.5179
0.7892
0.4236
2.0
2018
0.4775
0.8009
0.2732
3.0
3027
0.5075
0.8017
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3
