nyu-mll/glue
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How to use gchhablani/fnet-large-finetuned-stsb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gchhablani/fnet-large-finetuned-stsb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gchhablani/fnet-large-finetuned-stsb")
model = AutoModelForSequenceClassification.from_pretrained("gchhablani/fnet-large-finetuned-stsb", device_map="auto")This model is a fine-tuned version of google/fnet-large on the GLUE STSB dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 1.0727 | 1.0 | 1438 | 0.7718 | 0.8187 | 0.8240 | 0.8214 |
| 0.4619 | 2.0 | 2876 | 0.7704 | 0.8472 | 0.8500 | 0.8486 |
| 0.2401 | 3.0 | 4314 | 0.6250 | 0.8554 | 0.8533 | 0.8543 |