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README.md
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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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- samsum
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metrics:
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- rouge
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model-index:
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- name: t5-samsung-5e
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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: samsum
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type: samsum
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config: samsum
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split: train
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args: samsum
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metrics:
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- name: Rouge1
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type: rouge
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value: 43.1484
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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-samsung-5e
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7108
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- Rouge1: 43.1484
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- Rouge2: 20.4563
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- Rougel: 36.6379
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- Rougelsum: 40.196
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- Gen Len: 16.7677
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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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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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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- 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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| 1.873 | 1.0 | 1841 | 1.7460 | 41.7428 | 19.2191 | 35.2428 | 38.8578 | 16.7286 |
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| 1.8627 | 2.0 | 3682 | 1.7268 | 42.4494 | 19.8301 | 36.1459 | 39.5271 | 16.6039 |
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| 1.8293 | 3.0 | 5523 | 1.7223 | 42.8908 | 19.9782 | 36.1848 | 39.8482 | 16.7164 |
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| 1.8163 | 4.0 | 7364 | 1.7101 | 43.2291 | 20.3177 | 36.6418 | 40.2878 | 16.8472 |
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| 1.8174 | 5.0 | 9205 | 1.7108 | 43.1484 | 20.4563 | 36.6379 | 40.196 | 16.7677 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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