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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- govreport-summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: led-large-16384-govreport |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: govreport-summarization |
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type: govreport-summarization |
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config: document |
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split: validation |
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args: document |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.5194151586540673 |
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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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# led-large-16384-govreport |
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the govreport-summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7624 |
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- Rouge1: 0.5194 |
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- Rouge2: 0.2107 |
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- Rougel: 0.2437 |
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- Rougelsum: 0.2437 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 1.8152 | 3.65 | 500 | 1.7956 | 0.5095 | 0.2040 | 0.2382 | 0.2381 | |
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| 1.6981 | 3.66 | 1000 | 1.7624 | 0.5194 | 0.2107 | 0.2437 | 0.2437 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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