EdinburghNLP/xsum
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How to use autoevaluate/summarization-not-evaluated with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "summarization" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("summarization", model="autoevaluate/summarization-not-evaluated") # Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("autoevaluate/summarization-not-evaluated")
model = AutoModelForSeq2SeqLM.from_pretrained("autoevaluate/summarization-not-evaluated")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 |
|---|---|---|---|---|---|---|---|---|
| 2.9249 | 0.08 | 1000 | 2.6690 | 23.9405 | 5.0879 | 18.4981 | 18.5032 | 18.7376 |