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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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- arxiv-summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-base-axriv-to-abstract-3 |
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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: arxiv-summarization |
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type: arxiv-summarization |
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config: section |
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split: validation |
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args: section |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.1301 |
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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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# t5-base-axriv-to-abstract-3 |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the arxiv-summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6588 |
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- Rouge1: 0.1301 |
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- Rouge2: 0.0481 |
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- Rougel: 0.1047 |
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- Rougelsum: 0.1047 |
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- Gen Len: 19.0 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 3 |
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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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| 2.5634 | 0.61 | 4000 | 2.4010 | 0.1339 | 0.0519 | 0.1074 | 0.1075 | 19.0 | |
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| 2.4533 | 1.21 | 8000 | 2.3582 | 0.1318 | 0.0517 | 0.1067 | 0.1067 | 19.0 | |
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| 3.0109 | 1.82 | 12000 | 2.7488 | 0.1366 | 0.0509 | 0.1096 | 0.1095 | 18.9963 | |
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| 2.9063 | 2.42 | 16000 | 2.6588 | 0.1301 | 0.0481 | 0.1047 | 0.1047 | 19.0 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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