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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: bart-samsum |
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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: 0.4835 |
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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-samsum |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5071 |
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- Rouge1: 0.4835 |
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- Rouge2: 0.2546 |
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- Rougel: 0.4128 |
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- Rougelsum: 0.4131 |
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- Gen Len: 17.9817 |
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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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- 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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- 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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| 1.8082 | 1.0 | 2947 | 1.5613 | 0.4763 | 0.2412 | 0.4043 | 0.4041 | 17.9332 | |
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| 1.5609 | 2.0 | 5894 | 1.5206 | 0.4827 | 0.2485 | 0.4082 | 0.4085 | 18.3169 | |
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| 1.4228 | 3.0 | 8841 | 1.5008 | 0.4851 | 0.2557 | 0.4138 | 0.4137 | 17.9851 | |
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| 1.3131 | 4.0 | 11788 | 1.5071 | 0.4835 | 0.2546 | 0.4128 | 0.4131 | 17.9817 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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