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--- |
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license: mit |
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tags: |
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- summarization |
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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-base-cnn-xsum-wiki-swe |
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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-base-cnn-xsum-wiki-swe |
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This model is a fine-tuned version of [Gabriel/bart-base-cnn-xsum-swe](https://huggingface.co/Gabriel/bart-base-cnn-xsum-swe) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3884 |
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- Rouge1: 26.8917 |
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- Rouge2: 11.8254 |
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- Rougel: 22.6089 |
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- Rougelsum: 26.1492 |
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- Gen Len: 19.3468 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 9 |
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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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| 2.4993 | 1.0 | 2985 | 2.3834 | 25.8959 | 10.9373 | 21.8329 | 25.2002 | 19.1416 | |
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| 2.2397 | 2.0 | 5970 | 2.2939 | 26.1166 | 11.4087 | 22.2444 | 25.4752 | 19.2351 | |
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| 2.0318 | 3.0 | 8955 | 2.2687 | 26.5222 | 11.6512 | 22.567 | 25.851 | 19.2384 | |
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| 1.879 | 4.0 | 11940 | 2.2750 | 26.7637 | 11.7676 | 22.6674 | 26.0753 | 19.2622 | |
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| 1.7532 | 5.0 | 14925 | 2.2923 | 26.8104 | 11.8724 | 22.6794 | 26.0907 | 19.3063 | |
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| 1.6315 | 6.0 | 17910 | 2.3190 | 26.7758 | 11.7989 | 22.5925 | 26.032 | 19.3136 | |
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| 1.5409 | 7.0 | 20895 | 2.3517 | 26.8762 | 11.8552 | 22.6694 | 26.1329 | 19.3275 | |
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| 1.4711 | 8.0 | 23880 | 2.3679 | 26.899 | 11.9185 | 22.6764 | 26.1574 | 19.2994 | |
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| 1.4105 | 9.0 | 26865 | 2.3884 | 26.8917 | 11.8254 | 22.6089 | 26.1492 | 19.3468 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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