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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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