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albert-large-v2_cls_CR – AI Model by ghatgetanuj | AlphaNeural AI | AlphaNeural AI
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ghatgetanuj
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albert-large-v2_cls_CR
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transformers
pytorch
tensorboard
albert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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albert-large-v2_cls_CR
This model is a fine-tuned version of
albert-large-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6549
Accuracy: 0.6383
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: cosine
lr_scheduler_warmup_ratio: 0.2
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
213
0.3524
0.8803
No log
2.0
426
0.6839
0.6383
0.5671
3.0
639
0.6622
0.6383
0.5671
4.0
852
0.6549
0.6383
0.6652
5.0
1065
0.6549
0.6383
Framework versions
Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
