nyu-mll/glue
Viewer • Updated • 1.49M • 481k • 501
How to use lyrisha/distilbert-base-finetuned-sentiment with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="lyrisha/distilbert-base-finetuned-sentiment") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("lyrisha/distilbert-base-finetuned-sentiment")
model = AutoModelForSequenceClassification.from_pretrained("lyrisha/distilbert-base-finetuned-sentiment")This model is a fine-tuned version of lyrisha/distilbert-base-finetuned-imdb-sentiment on an imdb and GLUE SST2 dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1715 | 1.0 | 2105 | 0.2463 | 0.9106 |
| 0.1114 | 2.0 | 4210 | 0.3239 | 0.9037 |
| 0.0755 | 3.0 | 6315 | 0.3579 | 0.9128 |
Base model
distilbert/distilbert-base-uncased