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.
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
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