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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-3-8
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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-3-8
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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: 1.4132
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- Rouge1: 49.6606
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- Rouge2: 28.4044
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- Rougel: 31.5419
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- Rougelsum: 46.2463
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- Gen Len: 142.0
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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 | 258 | 1.2686 | 48.8513 | 28.7007 | 31.1199 | 45.7318 | 142.0 |
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| 1.1738 | 2.0 | 516 | 1.1884 | 49.8072 | 28.9817 | 31.3611 | 46.9639 | 141.6875 |
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| 1.1738 | 3.0 | 774 | 1.1970 | 49.3865 | 28.3426 | 30.0945 | 46.4681 | 141.3438 |
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| 0.7069 | 4.0 | 1032 | 1.1984 | 50.6743 | 29.4728 | 31.5364 | 47.989 | 141.7188 |
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| 0.7069 | 5.0 | 1290 | 1.2494 | 49.4461 | 28.9295 | 31.0334 | 46.6611 | 142.0 |
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| 0.4618 | 6.0 | 1548 | 1.2954 | 50.6789 | 30.2783 | 32.1932 | 47.5929 | 142.0 |
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| 0.4618 | 7.0 | 1806 | 1.3638 | 49.9476 | 30.223 | 32.4346 | 46.7383 | 142.0 |
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| 0.3293 | 8.0 | 2064 | 1.4132 | 49.6606 | 28.4044 | 31.5419 | 46.2463 | 142.0 |
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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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