| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: BART_corrector_15 |
| | 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_15 |
| |
|
| | This model is a fine-tuned version of [ainize/bart-base-cnn](https://huggingface.co/ainize/bart-base-cnn) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0214 |
| | - Rouge1: 80.3263 |
| | - Rouge2: 78.1274 |
| | - Rougel: 80.3215 |
| | - Rougelsum: 80.3039 |
| | - Gen Len: 19.3993 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## 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: 5 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | | 0.0597 | 1.0 | 2365 | 0.0367 | 79.3503 | 76.3308 | 79.32 | 79.3005 | 19.3992 | |
| | | 0.0322 | 2.0 | 4730 | 0.0276 | 79.9515 | 77.4211 | 79.9331 | 79.9164 | 19.3983 | |
| | | 0.0212 | 3.0 | 7095 | 0.0241 | 80.1413 | 77.8084 | 80.129 | 80.1098 | 19.3992 | |
| | | 0.0148 | 4.0 | 9460 | 0.0219 | 80.2625 | 78.035 | 80.2579 | 80.2372 | 19.4 | |
| | | 0.0111 | 5.0 | 11825 | 0.0214 | 80.3263 | 78.1274 | 80.3215 | 80.3039 | 19.3993 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.21.1 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.4.0 |
| | - Tokenizers 0.12.1 |
| |
|
