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--- |
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base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- learn3r/gov_report_memsum_bp |
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metrics: |
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- rouge |
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model-index: |
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- name: longt5_xl_gov_memsum_bp_20 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: learn3r/gov_report_memsum_bp |
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type: learn3r/gov_report_memsum_bp |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 42.5601 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# longt5_xl_gov_memsum_bp_20 |
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This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360](https://huggingface.co//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360) on the learn3r/gov_report_memsum_bp dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6259 |
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- Rouge1: 42.5601 |
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- Rouge2: 14.1791 |
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- Rougel: 17.9691 |
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- Rougelsum: 40.487 |
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- Gen Len: 1510.8695 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:---------:| |
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| 0.1591 | 1.0 | 136 | 3.6259 | 42.5601 | 14.1791 | 17.9691 | 40.487 | 1510.8695 | |
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| 0.1186 | 1.99 | 272 | 3.7885 | 39.795 | 13.2493 | 17.3095 | 37.9065 | 1707.0401 | |
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| 0.097 | 3.0 | 409 | 4.0192 | 41.4441 | 13.4026 | 17.8804 | 39.4502 | 1442.7729 | |
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| 0.0818 | 4.0 | 545 | 4.1699 | 40.2374 | 13.5869 | 17.364 | 38.2969 | 1741.0236 | |
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| 0.0786 | 4.99 | 680 | 4.3339 | 39.5612 | 13.4283 | 17.3666 | 37.6526 | 1710.4111 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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