learn3r/gov_report_memsum_oracle
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How to use learn3r/longt5_xl_gov_report_bp_10_continue with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("learn3r/longt5_xl_gov_report_bp_10_continue")
model = AutoModelForSeq2SeqLM.from_pretrained("learn3r/longt5_xl_gov_report_bp_10_continue")YAML Metadata Error:"base_model" with value "/home/co-ou1/rds/hpc-work/transformers/examples/pytorch/summarization/longt5_xl_gov_report_bp_10/checkpoint-477" is not valid. Use a model id from https://hf.co/models.
This model is a fine-tuned version of /home/co-ou1/rds/hpc-work/transformers/examples/pytorch/summarization/longt5_xl_gov_report_bp_10/checkpoint-477 on the learn3r/gov_report_memsum_oracle 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 |
|---|---|---|---|---|---|---|---|---|
| 0.6226 | 1.0 | 68 | 1.4878 | 71.9439 | 43.7031 | 41.8301 | 69.1853 | 833.0319 |
| 0.4983 | 1.99 | 136 | 1.5908 | 70.6191 | 43.2627 | 42.581 | 68.0871 | 627.5031 |
| 0.4175 | 2.99 | 204 | 1.6407 | 71.6704 | 43.1655 | 41.9746 | 68.992 | 737.4352 |
| 0.3958 | 3.99 | 272 | 1.8739 | 70.7685 | 42.5122 | 41.7454 | 68.0785 | 671.4938 |