textattack / albert-base-v2-snli

huggingface.co
Total runs: 101
24-hour runs: -4
7-day runs: -12
30-day runs: 68
Model's Last Updated: July 07 2020
text-classification

Introduction of albert-base-v2-snli

Model Details of albert-base-v2-snli

TextAttack Model Card

This albert-base-v2 model was fine-tuned for sequence classification using TextAttack and the snli dataset loaded using the nlp library. The model was fine-tuned for 5 epochs with a batch size of 64, a learning rate of 2e-05, and a maximum sequence length of 64. Since this was a classification task, the model was trained with a cross-entropy loss function. The best score the model achieved on this task was 0.9060150375939849, as measured by the eval set accuracy, found after 2 epochs.

For more information, check out TextAttack on Github .

Runs of textattack albert-base-v2-snli on huggingface.co

101
Total runs
-4
24-hour runs
-10
3-day runs
-12
7-day runs
68
30-day runs

More Information About albert-base-v2-snli huggingface.co Model

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Url of albert-base-v2-snli

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