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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-4-8 |
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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-4-8 |
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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: 0.7790 |
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- Rouge1: 54.3036 |
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- Rouge2: 37.1443 |
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- Rougel: 40.4762 |
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- Rougelsum: 52.1796 |
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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 | 398 | 0.9580 | 52.5184 | 33.0208 | 35.0634 | 49.9083 | 142.0 | |
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| 1.119 | 2.0 | 796 | 0.8356 | 53.0801 | 34.5549 | 36.9807 | 50.3394 | 141.2963 | |
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| 0.6814 | 3.0 | 1194 | 0.7968 | 53.9433 | 34.8086 | 36.7654 | 51.3384 | 142.0 | |
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| 0.4623 | 4.0 | 1592 | 0.7474 | 53.947 | 36.2662 | 39.332 | 51.7559 | 142.0 | |
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| 0.4623 | 5.0 | 1990 | 0.7563 | 54.5816 | 37.0675 | 40.3592 | 52.2391 | 142.0 | |
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| 0.3228 | 6.0 | 2388 | 0.7383 | 54.787 | 37.3647 | 40.521 | 52.3113 | 142.0 | |
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| 0.2183 | 7.0 | 2786 | 0.7606 | 54.1822 | 37.6748 | 40.7956 | 52.1102 | 141.7778 | |
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| 0.1759 | 8.0 | 3184 | 0.7790 | 54.3036 | 37.1443 | 40.4762 | 52.1796 | 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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