stanfordnlp/imdb
Viewer • Updated • 100k • 178k • 370
How to use dfurman/deberta-v3-base-imdb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="dfurman/deberta-v3-base-imdb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("dfurman/deberta-v3-base-imdb")
model = AutoModelForSequenceClassification.from_pretrained("dfurman/deberta-v3-base-imdb")This model is a fine-tuned version of microsoft/deberta-v3-base on the imdb 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3108 | 1.0 | 12500 | 0.2634 | 0.9530 | 0.9529 | 0.9557 | 0.9502 |
| 0.2322 | 2.0 | 25000 | 0.2629 | 0.9546 | 0.9552 | 0.9437 | 0.9670 |
| 0.1119 | 3.0 | 37500 | 0.2944 | 0.9546 | 0.9550 | 0.9467 | 0.9634 |
| 0.0292 | 4.0 | 50000 | 0.3694 | 0.9557 | 0.9564 | 0.9422 | 0.9710 |
| 0.0191 | 5.0 | 62500 | 0.3594 | 0.9577 | 0.9579 | 0.9530 | 0.9629 |
Base model
microsoft/deberta-v3-base