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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- big_patent |
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metrics: |
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- rouge |
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model-index: |
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- name: nd_pegasus_bigpatent_cnn_xsum_model |
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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: big_patent |
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type: big_patent |
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config: d |
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split: train[:200] |
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args: d |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.3465 |
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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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# nd_pegasus_bigpatent_cnn_xsum_model |
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This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the big_patent dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1037 |
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- Rouge1: 0.3465 |
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- Rouge2: 0.1181 |
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- Rougel: 0.2258 |
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- Rougelsum: 0.227 |
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- Gen Len: 85.75 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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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: 2 |
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- mixed_precision_training: Native AMP |
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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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| 3.5734 | 1.0 | 80 | 3.1804 | 0.3468 | 0.1231 | 0.2262 | 0.2268 | 89.95 | |
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| 3.3146 | 2.0 | 160 | 3.1037 | 0.3465 | 0.1181 | 0.2258 | 0.227 | 85.75 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.2 |
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