FiscalNote/billsum
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How to use phi0108/summarization with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("phi0108/summarization")
model = AutoModelForSeq2SeqLM.from_pretrained("phi0108/summarization")This model is a fine-tuned version of t5-small on the billsum 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.7907 | 0.1226 | 0.0355 | 0.1036 | 0.1034 | 19.0 |
| No log | 2.0 | 124 | 2.5804 | 0.1343 | 0.0468 | 0.1126 | 0.1125 | 19.0 |
| No log | 3.0 | 186 | 2.5159 | 0.1441 | 0.0549 | 0.1198 | 0.1197 | 19.0 |
| No log | 4.0 | 248 | 2.4987 | 0.1453 | 0.0544 | 0.1203 | 0.1202 | 19.0 |