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nbme-xlnet-large-cased – AI Model by smeoni | AlphaNeural AI
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smeoni
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nbme-xlnet-large-cased
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transformers
pytorch
tensorboard
xlnet
text-generation
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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nbme-xlnet-large-cased
This model is a fine-tuned version of
xlnet-large-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.7151
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
2.2931
1.0
1850
1.9915
1.9467
2.0
3700
1.7866
1.7983
3.0
5550
1.6919
Framework versions
Transformers 4.19.0.dev0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
