This
albert-base-v2
model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the
nlp
library. The model was fine-tuned
for 5 epochs with a batch size of 64, a learning
rate of 3e-05, and a maximum sequence length of 128.
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 0.776173285198556, as measured by the
eval set accuracy, found after 4 epochs.
Runs of textattack albert-base-v2-RTE on huggingface.co
43
Total runs
0
24-hour runs
0
3-day runs
3
7-day runs
2
30-day runs
More Information About albert-base-v2-RTE huggingface.co Model
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