EdinburghNLP/xsum
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How to use Hemantjangra/bart-base-finetuned-xsum with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Hemantjangra/bart-base-finetuned-xsum")
model = AutoModelForSeq2SeqLM.from_pretrained("Hemantjangra/bart-base-finetuned-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 | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.4765 | 1.0 | 1000 | 2.0873 | 33.9596 | 12.722 | 27.4135 | 27.4062 |
| 1.9854 | 2.0 | 2000 | 2.0802 | 33.6802 | 12.8965 | 27.4061 | 27.4064 |
| 1.6677 | 3.0 | 3000 | 2.0998 | 34.2038 | 13.1362 | 27.8808 | 27.8806 |
| 1.4313 | 4.0 | 4000 | 2.1404 | 34.8491 | 13.4154 | 28.2768 | 28.2702 |
| 1.275 | 5.0 | 5000 | 2.1755 | 34.6293 | 13.4749 | 28.2616 | 28.2553 |