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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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- summarization
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- generated_from_trainer
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datasets:
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- cnn_dailymail
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metrics:
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- rouge
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model-index:
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- name: t5-v1_1-small-finetuned-cnn_dailymail
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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: cnn_dailymail
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type: cnn_dailymail
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config: 3.0.0
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split: train
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args: 3.0.0
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metrics:
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- name: Rouge1
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type: rouge
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value: 0.3362804924711526
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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-v1_1-small-finetuned-cnn_dailymail
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This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the cnn_dailymail dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7290
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- Rouge1: 0.3363
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- Rouge2: 0.1736
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- Rougel: 0.2951
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- Rougelsum: 0.3151
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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: 5.6e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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: 4
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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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| 2.7338 | 1.0 | 35890 | 1.8390 | 0.3278 | 0.1658 | 0.2876 | 0.3064 |
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| 2.3233 | 2.0 | 71780 | 1.7779 | 0.3335 | 0.1713 | 0.2924 | 0.3124 |
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| 2.2253 | 3.0 | 107670 | 1.7428 | 0.3348 | 0.1728 | 0.2941 | 0.3138 |
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| 2.1797 | 4.0 | 143560 | 1.7290 | 0.3363 | 0.1736 | 0.2951 | 0.3151 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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