FiscalNote/billsum
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How to use foscraft/ca-t5-67 with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("foscraft/ca-t5-67")
model = AutoModelForSeq2SeqLM.from_pretrained("foscraft/ca-t5-67")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 | 2.8375 | 0.1251 | 0.0354 | 0.1041 | 0.1043 | 19.0 |
| No log | 2.0 | 124 | 2.6198 | 0.1371 | 0.0465 | 0.1122 | 0.1121 | 19.0 |
| No log | 3.0 | 186 | 2.5564 | 0.1429 | 0.0511 | 0.1152 | 0.115 | 19.0 |
| No log | 4.0 | 248 | 2.5391 | 0.1437 | 0.0507 | 0.1161 | 0.1159 | 19.0 |
Base model
google-t5/t5-small