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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: finetuned_on_citesum_bart_text_summarisation |
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results: [] |
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datasets: |
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- yuningm/citesum |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: summarization |
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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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# finetuned_on_citesum_bart_text_summarisation |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3597 |
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- Rouge1: 0.3541 |
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- Rouge2: 0.1548 |
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- Rougel: 0.2659 |
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- Rougelsum: 0.2657 |
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- Gen Len: 67.0143 |
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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: 3 |
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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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| No log | 1.0 | 350 | 0.3449 | 0.3492 | 0.1554 | 0.2685 | 0.268 | 68.7357 | |
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| 0.5359 | 2.0 | 700 | 0.3458 | 0.3516 | 0.1531 | 0.2647 | 0.2646 | 67.0714 | |
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| 0.2219 | 3.0 | 1050 | 0.3597 | 0.3541 | 0.1548 | 0.2659 | 0.2657 | 67.0143 | |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.13.3 |
