EdinburghNLP/xsum
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How to use mayjul/t5-small-finetuned-xsum with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("mayjul/t5-small-finetuned-xsum")
model = AutoModelForSeq2SeqLM.from_pretrained("mayjul/t5-small-finetuned-xsum", device_map="auto")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 |
|---|---|---|---|---|---|---|---|---|
| 2.7189 | 1.0 | 12753 | 2.4789 | 28.2727 | 7.7068 | 22.1993 | 22.2071 | 18.8238 |