EdinburghNLP/xsum
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How to use alexrodpas/T5-XSum-base with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("alexrodpas/T5-XSum-base")
model = AutoModelForSeq2SeqLM.from_pretrained("alexrodpas/T5-XSum-base")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 |
|---|---|---|---|---|---|---|---|---|
| 2.8234 | 1.0 | 2041 | 2.5916 | 0.2623 | 0.0647 | 0.2043 | 0.2044 | 18.8152 |
| 2.7742 | 2.0 | 4082 | 2.5577 | 0.2707 | 0.0702 | 0.2118 | 0.2117 | 18.8212 |
| 2.7482 | 3.0 | 6123 | 2.5491 | 0.273 | 0.0711 | 0.2134 | 0.2134 | 18.8194 |
Base model
google-t5/t5-small