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--- |
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license: mit |
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base_model: facebook/bart-large-cnn |
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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: PTS-Bart-Large-CNN |
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results: |
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- task: |
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type: summarization |
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name: Summarization |
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dataset: |
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name: PTS Dataset |
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type: PTS-Dataset |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.6551 |
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- name: Rouge2 |
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type: rouge |
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value: 0.4332 |
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- name: Rougel |
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type: rouge |
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value: 0.5543 |
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- name: Rougelsum |
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type: rouge |
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value: 0.5541 |
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datasets: |
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- ahmedmbutt/PTS-Dataset |
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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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widget: |
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- text: >- |
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I have to say that I do miss talking to a good psychiatrist- however. I |
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could sit and argue for ages with a psychiatrist who is intelligent and kind |
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(quite hard to find- but they do exist). Especially now that I have a PhD in |
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philosophy and have read everything that can be found on madness- including |
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the notes they wrote about me when I was in the hospital. Nowadays- |
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psychiatrists have a tendency to sign me off pretty quickly when I come onto |
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their radar. They don’t wish to deal with me- I tire them out. |
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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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# PTS-Bart-Large-CNN |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the PTS dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1760 |
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- Rouge1: 0.6551 |
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- Rouge2: 0.4332 |
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- Rougel: 0.5543 |
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- Rougelsum: 0.5541 |
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- Gen Len: 80.0886 |
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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: 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: 8 |
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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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| No log | 1.0 | 220 | 0.8239 | 0.6263 | 0.3973 | 0.5238 | 0.5237 | 84.2023 | |
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| No log | 2.0 | 440 | 0.8201 | 0.6461 | 0.4184 | 0.5417 | 0.5416 | 81.1659 | |
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| 0.7121 | 3.0 | 660 | 0.8661 | 0.6479 | 0.4226 | 0.5448 | 0.5454 | 80.5409 | |
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| 0.7121 | 4.0 | 880 | 0.9784 | 0.6474 | 0.4242 | 0.5424 | 0.5425 | 82.2932 | |
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| 0.2619 | 5.0 | 1100 | 1.0645 | 0.655 | 0.4327 | 0.5517 | 0.5517 | 80.8386 | |
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| 0.2619 | 6.0 | 1320 | 1.1098 | 0.6548 | 0.4339 | 0.5542 | 0.5543 | 81.3545 | |
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| 0.1124 | 7.0 | 1540 | 1.1528 | 0.6528 | 0.4298 | 0.5511 | 0.551 | 80.5705 | |
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| 0.1124 | 8.0 | 1760 | 1.1760 | 0.6551 | 0.4332 | 0.5543 | 0.5541 | 80.0886 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
