EdinburghNLP/xsum
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How to use hassaanshafqat/bart-xsum with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="hassaanshafqat/bart-xsum") # Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("hassaanshafqat/bart-xsum")
model = AutoModel.from_pretrained("hassaanshafqat/bart-xsum")This model is a fine-tuned version of facebook/bart-base on the xsum 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 |
|---|---|---|---|
| 0.1699 | 1.0 | 250 | 0.1267 |
| 0.1294 | 2.0 | 500 | 0.1141 |
| 0.1187 | 3.0 | 750 | 0.1135 |
Base model
facebook/bart-base