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update model card README.md
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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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metrics:
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- rouge
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model-index:
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- name: bart-large-cnn-finetuned-roundup-8
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results: []
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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-large-cnn-finetuned-roundup-8
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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: 1.4519
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- Rouge1: 49.5671
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- Rouge2: 27.0118
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- Rougel: 30.8538
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- Rougelsum: 45.5503
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- Gen Len: 141.75
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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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- 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 | 132 | 1.3159 | 48.5275 | 28.0817 | 30.6646 | 45.5024 | 142.0 |
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| No log | 2.0 | 264 | 1.2377 | 47.0791 | 27.4386 | 28.9458 | 44.1536 | 142.0 |
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| No log | 3.0 | 396 | 1.2474 | 49.3567 | 29.5904 | 30.8029 | 46.6083 | 142.0 |
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| 0.9623 | 4.0 | 528 | 1.2914 | 47.8795 | 27.0611 | 29.8538 | 44.4494 | 142.0 |
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| 0.9623 | 5.0 | 660 | 1.2982 | 49.9921 | 28.4839 | 31.5688 | 46.9734 | 142.0 |
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| 0.9623 | 6.0 | 792 | 1.3521 | 46.7269 | 25.8672 | 29.7325 | 43.8279 | 142.0 |
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| 0.9623 | 7.0 | 924 | 1.4102 | 47.4995 | 26.0066 | 29.4342 | 44.1102 | 141.8 |
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| 0.3734 | 8.0 | 1056 | 1.4519 | 49.5671 | 27.0118 | 30.8538 | 45.5503 | 141.75 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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