EdinburghNLP/xsum
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How to use srivathsa96/t5-small-summary-extract with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("srivathsa96/t5-small-summary-extract")
model = AutoModelForSeq2SeqLM.from_pretrained("srivathsa96/t5-small-summary-extract")This model is a fine-tuned version of t5-small 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7071 | 1.0 | 12753 | 2.4781 | 28.295 | 7.7327 | 22.2414 | 22.2486 | 18.8252 |
Base model
google-t5/t5-small