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Gabriel
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bart-base-cnn-xsum-swe

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Transformers
PyTorch
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Swedish
bart
text2text-generation
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update model card README.md

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@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Gabriel/bart-base-cnn-swe](https://huggingface.co/Gabriel/bart-base-cnn-swe) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.1140
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- - Rouge1: 30.7101
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- - Rouge2: 11.9532
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- - Rougel: 25.1864
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- - Rougelsum: 25.2227
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- - Gen Len: 19.7448
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3.75e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -49,21 +49,22 @@ The following hyperparameters were used during training:
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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: 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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- | 2.3087 | 1.0 | 6375 | 2.1997 | 29.7666 | 11.0222 | 24.2659 | 24.2915 | 19.7172 |
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- | 2.0793 | 2.0 | 12750 | 2.1285 | 30.4447 | 11.7671 | 24.9238 | 24.9622 | 19.7051 |
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- | 1.9186 | 3.0 | 19125 | 2.1140 | 30.7101 | 11.9532 | 25.1864 | 25.2227 | 19.7448 |
 
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  ### Framework versions
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- - Transformers 4.22.1
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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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  This model is a fine-tuned version of [Gabriel/bart-base-cnn-swe](https://huggingface.co/Gabriel/bart-base-cnn-swe) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1027
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+ - Rouge1: 30.9467
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+ - Rouge2: 12.2589
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+ - Rougel: 25.4487
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+ - Rougelsum: 25.4792
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+ - Gen Len: 19.7379
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 4e-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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  - 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: 4
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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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+ | 2.3076 | 1.0 | 6375 | 2.1986 | 29.7041 | 10.9883 | 24.2149 | 24.2406 | 19.7193 |
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+ | 2.0733 | 2.0 | 12750 | 2.1246 | 30.4521 | 11.8107 | 24.9519 | 24.9745 | 19.6592 |
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+ | 1.8933 | 3.0 | 19125 | 2.0989 | 30.9407 | 12.2682 | 25.4135 | 25.4378 | 19.7195 |
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+ | 1.777 | 4.0 | 25500 | 2.1027 | 30.9467 | 12.2589 | 25.4487 | 25.4792 | 19.7379 |
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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