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bert-base-uncased-finetuned-wls-manual-8ep-lower – AI Model by btamm12 | AlphaNeural AI
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btamm12
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bert-base-uncased-finetuned-wls-manual-8ep-lower
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transformers
pytorch
tensorboard
bert
fill-mask
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-finetuned-wls-manual-8ep-lower
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3345
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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8
Training results
Training Loss
Epoch
Step
Validation Loss
2.1106
0.93
7
1.9471
1.5981
2.0
15
1.5742
1.4773
2.93
22
1.4429
1.3774
4.0
30
1.4203
1.2795
4.93
37
1.2554
1.2611
6.0
45
1.2564
1.2301
6.93
52
1.2837
1.1744
7.47
56
1.3219
Framework versions
Transformers 4.31.0
Pytorch 1.11.0+cu113
Datasets 2.14.4
Tokenizers 0.13.3
