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README.md
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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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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: 51.7796
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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: 0.4048
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- Rouge1: 51.7796
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- Rouge2: 26.1341
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- Rougel: 41.4013
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- Rougelsum: 41.4563
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- Gen Len: 29.656
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 2
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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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- 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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| 0.5781 | 1.0 | 500 | 0.3637 | 50.8871 | 26.6178 | 41.8757 | 41.9291 | 25.16 |
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| 0.2183 | 2.0 | 1000 | 0.3586 | 50.7919 | 25.4277 | 40.8428 | 40.8421 | 27.712 |
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| 0.1354 | 3.0 | 1500 | 0.4048 | 51.7796 | 26.1341 | 41.4013 | 41.4563 | 29.656 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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