FiscalNote/billsum
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How to use thanhnamitit/my_awesome_billsum_model with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("thanhnamitit/my_awesome_billsum_model")
model = AutoModelForSeq2SeqLM.from_pretrained("thanhnamitit/my_awesome_billsum_model", device_map="auto")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 | 2.8464 | 0.1221 | 0.0329 | 0.101 | 0.101 | 19.0 |
| No log | 2.0 | 124 | 2.6342 | 0.1311 | 0.0426 | 0.1078 | 0.1076 | 19.0 |
| No log | 3.0 | 186 | 2.5714 | 0.1375 | 0.0502 | 0.113 | 0.1127 | 19.0 |
| No log | 4.0 | 248 | 2.5545 | 0.1376 | 0.0498 | 0.1127 | 0.1122 | 19.0 |
Base model
google-t5/t5-small