nyu-mll/glue
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How to use mrm8488/data2vec-text-base-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mrm8488/data2vec-text-base-finetuned-sst2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mrm8488/data2vec-text-base-finetuned-sst2")
model = AutoModelForSequenceClassification.from_pretrained("mrm8488/data2vec-text-base-finetuned-sst2")This model is a fine-tuned version of facebook/data2vec-text-base on the glue 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 | Accuracy |
|---|---|---|---|---|
| 0.2865 | 1.0 | 4210 | 0.2662 | 0.9128 |
| 0.2256 | 2.0 | 8420 | 0.3698 | 0.9002 |
| 0.1676 | 3.0 | 12630 | 0.3107 | 0.9186 |
| 0.1481 | 4.0 | 16840 | 0.3425 | 0.9186 |
| 0.1429 | 5.0 | 21050 | 0.3600 | 0.9232 |