FiscalNote/billsum
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How to use jnelen/output with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("jnelen/output")
model = AutoModelForSeq2SeqLM.from_pretrained("jnelen/output", device_map="auto")This model is a fine-tuned version of google/flan-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 | 2.2470 | 0.1958 | 0.0948 | 0.1648 | 0.1645 | 18.9798 |
| No log | 2.0 | 124 | 2.1637 | 0.1983 | 0.0963 | 0.1673 | 0.167 | 19.0 |
| No log | 3.0 | 186 | 2.1299 | 0.1954 | 0.0959 | 0.166 | 0.1658 | 19.0 |
| No log | 4.0 | 248 | 2.1078 | 0.1949 | 0.0948 | 0.1663 | 0.1662 | 19.0 |
| No log | 5.0 | 310 | 2.1039 | 0.1949 | 0.0951 | 0.167 | 0.1668 | 19.0 |