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lumunot
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mbart-neutralization

Text2Text Generation
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mbart
simplification
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Training complete

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  1. README.md +10 -10
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0181
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- - Bleu: 98.7341
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- - Gen Len: 18.4896
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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- | No log | 1.0 | 440 | 0.0307 | 91.2911 | 18.25 |
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- | 0.2343 | 2.0 | 880 | 0.0181 | 98.7341 | 18.4896 |
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  ### Framework versions
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  - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.17.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.3176
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+ - Bleu: 10.687
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+ - Gen Len: 23.0244
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | No log | 1.0 | 31 | 3.6163 | 8.5266 | 23.7073 |
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+ | No log | 2.0 | 62 | 3.3176 | 10.687 | 23.0244 |
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  ### Framework versions
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  - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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  - Tokenizers 0.15.2
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