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xlnet-base-mnli-finetuned – AI Model by vish88 | AlphaNeural AI
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vish88
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xlnet-base-mnli-finetuned
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transformers
pytorch
tensorboard
xlnet
text-classification
generated_from_trainer
glue
mit
model-index
autotrain_compatible
endpoints_compatible
us
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xlnet-base-mnli-finetuned
This model is a fine-tuned version of
xlnet-base-cased
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.3456
Accuracy: 0.9119
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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.336
1.0
49087
0.3299
0.9010
0.2582
2.0
98174
0.3456
0.9119
Framework versions
Transformers 4.20.1
Pytorch 1.12.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1
