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 32, a learning
rate of 3e-05, and a maximum sequence length of 128.
Since this was a regression task, the model was trained with a mean squared error loss function.
The best score the model achieved on this task was 0.9064220351504577, as measured by the
eval set pearson correlation, found after 3 epochs.
Runs of textattack albert-base-v2-STS-B on huggingface.co
20
Total runs
0
24-hour runs
1
3-day runs
2
7-day runs
7
30-day runs
More Information About albert-base-v2-STS-B huggingface.co Model
albert-base-v2-STS-B huggingface.co
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textattack albert-base-v2-STS-B online free url in huggingface.co:
albert-base-v2-STS-B is an open source model from GitHub that offers a free installation service, and any user can find albert-base-v2-STS-B on GitHub to install. At the same time, huggingface.co provides the effect of albert-base-v2-STS-B install, users can directly use albert-base-v2-STS-B installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
albert-base-v2-STS-B install url in huggingface.co: