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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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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: cnn_dailymail_t5_small |
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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: default |
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split: train |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.2321 |
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--- |
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# cnn_dailymail_t5_small |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7271 |
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- Rouge1: 0.2321 |
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- Rouge2: 0.0955 |
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- Rougel: 0.1887 |
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- Rougelsum: 0.1887 |
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- Gen Len: 18.9998 |
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## Model description |
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Text-To-Text Transfer Transformer (T5) |
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T5-Small is the checkpoint with 60 million parameters. |
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## Intended uses & limitations |
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This is an exercise for finetuning of pretrained t5 model. |
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## Training and evaluation data |
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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: 2 |
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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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| 1.9158 | 1.0 | 10000 | 1.7333 | 0.2313 | 0.0948 | 0.1879 | 0.1879 | 18.9998 | |
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| 1.9316 | 2.0 | 20000 | 1.7271 | 0.2321 | 0.0955 | 0.1887 | 0.1887 | 18.9998 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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