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carmengoar
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t5-neutralisation

Transformers
Safetensors
t5
text2text-generation
simplification
Generated from Trainer
text-generation-inference
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carmengoar commited on
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Training complete

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  1. README.md +10 -8
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0743
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- - Bleu: 53.8876
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- - Gen Len: 18.6354
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  ## Model description
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@@ -46,16 +46,18 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 4
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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 | 0.1093 | 53.4609 | 18.6146 |
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- | 0.0779 | 2.0 | 880 | 0.0886 | 53.8469 | 18.6042 |
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- | 0.0641 | 3.0 | 1320 | 0.0791 | 54.0904 | 18.6667 |
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- | 0.0586 | 4.0 | 1760 | 0.0743 | 53.8876 | 18.6354 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0593
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+ - Bleu: 54.7416
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+ - Gen Len: 18.7292
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 6
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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 | 0.0837 | 53.9225 | 18.6042 |
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+ | 0.0369 | 2.0 | 880 | 0.0739 | 54.1449 | 18.6354 |
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+ | 0.034 | 3.0 | 1320 | 0.0690 | 54.4631 | 18.6562 |
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+ | 0.0346 | 4.0 | 1760 | 0.0625 | 54.7416 | 18.7292 |
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+ | 0.0423 | 5.0 | 2200 | 0.0599 | 54.7416 | 18.7292 |
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+ | 0.0406 | 6.0 | 2640 | 0.0593 | 54.7416 | 18.7292 |
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  ### Framework versions