stanfordnlp/snli
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How to use varun-v-rao/bart-large-snli-model1 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-model1") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("varun-v-rao/bart-large-snli-model1")
model = AutoModelForSequenceClassification.from_pretrained("varun-v-rao/bart-large-snli-model1")This model is a fine-tuned version of facebook/bart-large on the snli 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 |
|---|---|---|---|---|
| 0.3865 | 1.0 | 4292 | 0.2993 | 0.8906 |
| 0.3276 | 2.0 | 8584 | 0.2780 | 0.9018 |
| 0.2925 | 3.0 | 12876 | 0.2739 | 0.9052 |
Base model
facebook/bart-large