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bert-base-uncased-finetuned-wls-manual-5ep-lower – AI Model by btamm12 | AlphaNeural AI
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btamm12
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bert-base-uncased-finetuned-wls-manual-5ep-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-5ep-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: 1.4858
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
2.1142
0.93
7
1.9585
1.6082
2.0
15
1.5910
1.4973
2.93
22
1.4644
1.4145
4.0
30
1.4717
1.335
4.67
35
1.4035
Framework versions
Transformers 4.31.0
Pytorch 1.11.0+cu113
Datasets 2.14.4
Tokenizers 0.13.3
