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albert-base-v2-topic-abstract-classification – AI Model by Eitanli | AlphaNeural AI
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Eitanli
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albert-base-v2-topic-abstract-classification
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transformers
pytorch
albert
text-classification
generated_from_trainer
albert/albert-base-v2
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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albert-base-v2-topic-abstract-classification
This model is a fine-tuned version of
albert-base-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2814
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
0.3621
1.0
4992
0.4209
0.3058
2.0
9984
0.3028
0.2757
3.0
14976
0.2814
Framework versions
Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1
