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--- |
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license: mit |
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base_model: facebook/bart-large-xsum |
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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: conversation-summ |
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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: validation |
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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: 54.1736 |
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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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# conversation-summ |
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This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3078 |
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- Rouge1: 54.1736 |
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- Rouge2: 29.3773 |
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- Rougel: 44.1092 |
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- Rougelsum: 49.6189 |
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- Gen Len: 30.1443 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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: 1 |
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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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| 0.2428 | 1.0 | 3683 | 0.3078 | 54.1736 | 29.3773 | 44.1092 | 49.6189 | 30.1443 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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