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bert-large-uncased_finetuning_distillation – AI Model by ashabrawy | AlphaNeural AI
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ashabrawy
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bert-large-uncased_finetuning_distillation
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transformers
safetensors
bert
text-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
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bert-large-uncased_finetuning_distillation
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4721
Accuracy: 0.8352
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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.7395
1.39
500
0.8593
0.6847
0.6019
2.78
1000
0.5655
0.7949
0.3085
4.17
1500
0.4899
0.8293
0.1631
5.56
2000
0.4558
0.8475
Framework versions
Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1
