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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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- cnn_dailymail |
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metrics: |
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- rouge |
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model-index: |
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- name: bart-base-cnndm |
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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: test |
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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: 25.0336 |
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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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# bart-base-cnndm |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the cnn_dailymail dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5802 |
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- Rouge1: 25.0336 |
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- Rouge2: 12.5344 |
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- Rougel: 20.8721 |
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- Rougelsum: 23.5806 |
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- Gen Len: 19.9998 |
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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: 3e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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 | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 1.845 | 1.0 | 8972 | 1.6461 | 24.8325 | 12.327 | 20.6952 | 23.3653 | 19.9998 | |
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| 1.7427 | 2.0 | 17945 | 1.6098 | 24.9118 | 12.4577 | 20.786 | 23.4624 | 19.9998 | |
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| 1.6727 | 3.0 | 26917 | 1.5881 | 24.9723 | 12.4738 | 20.8317 | 23.5195 | 19.9994 | |
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| 1.6288 | 4.0 | 35888 | 1.5802 | 25.0336 | 12.5344 | 20.8721 | 23.5806 | 19.9998 | |
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### Framework versions |
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- Transformers 4.27.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.3 |
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