stanfordnlp/snli
Viewer • Updated • 570k • 23.4k • 93
How to use varun-v-rao/bart-large-snli-model3 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="varun-v-rao/bart-large-snli-model3") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("varun-v-rao/bart-large-snli-model3")
model = AutoModelForSequenceClassification.from_pretrained("varun-v-rao/bart-large-snli-model3")This model is a fine-tuned version of facebook/bart-large on the snli 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 |
|---|---|---|---|---|
| 0.2837 | 1.0 | 4292 | 0.2169 | 0.9247 |
| 0.2372 | 2.0 | 8584 | 0.2062 | 0.9321 |
| 0.1984 | 3.0 | 12876 | 0.2096 | 0.9311 |
Base model
facebook/bart-large