| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: BART_corrector |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # BART_corrector |
| |
| This model is a fine-tuned version of [ainize/bart-base-cnn](https://huggingface.co/ainize/bart-base-cnn) on a homemade dataset. Each sample of the dataset is an english sentence that has been duplicated 10 times and where random errors (7%) were added. |
| |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0025 |
| - Rouge1: 81.4214 |
| - Rouge2: 80.2027 |
| - Rougel: 81.4202 |
| - Rougelsum: 81.4241 |
| - Gen Len: 19.3962 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| The goal of this model is to correct a sentence, given several versions of it with various mistakes. |
| |
| Text sample : |
| _TheIdeSbgn of thh Eiffel Toweg is aYtribeted to Ma. . ahd design of The Eijfel Tower is attribQtedBto ta. . The designYof the EifZel Tower Vs APtWibuteQ to Ma. . The xeQign oC the EiffelXTower ik attributed to Ma. . ghebFesign of theSbiffel TJwer is atMributed to Ma. . The desOBn of thQ Eiffel ToweP isfattributnd toBMa. . The design of the EBfUel Fower is JtAriOuted tx Ma. . The design of Jhe ENffel LoweF is aptrVbuted Lo Ma. . The deslgX of the lPffel Towermis attributedhtohMa. . The desRgn of thekSuffel Tower is Ttkribufed to Ma. ._ |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | 0.0071 | 1.0 | 2365 | 0.0039 | 81.3664 | 80.0861 | 81.3601 | 81.3667 | 19.3967 | |
| | 0.0033 | 2.0 | 4730 | 0.0029 | 81.3937 | 80.1548 | 81.3902 | 81.3974 | 19.3961 | |
| | 0.0018 | 3.0 | 7095 | 0.0029 | 81.3838 | 80.1404 | 81.385 | 81.3878 | 19.3965 | |
| | 0.001 | 4.0 | 9460 | 0.0025 | 81.4214 | 80.2027 | 81.4202 | 81.4241 | 19.3962 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.21.1 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
