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esci-mlm-us-bert-base-uncased – AI Model by spacemanidol | AlphaNeural AI
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esci-mlm-us-bert-base-uncased
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transformers
pytorch
bert
fill-mask
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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esci-us-bert-base-uncased
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.1785
Accuracy: 0.7499
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: 0.0005
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 256
total_eval_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
Training results
Framework versions
Transformers 4.18.0.dev0
Pytorch 1.7.1+cu110
Datasets 1.18.0
Tokenizers 0.12.1
