| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: denoice-finetuned-xsum |
| 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. --> |
|
|
| # denoice-finetuned-xsum |
|
|
| This model was trained from scratch on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7176 |
| - Rouge1: 72.4979 |
| - Rouge2: 55.09 |
| - Rougel: 72.5668 |
| - Rougelsum: 72.5151 |
| - Gen Len: 16.5209 |
|
|
| ## 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: 500 |
| - eval_batch_size: 500 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | No log | 1.0 | 76 | 0.7237 | 72.7109 | 55.346 | 72.7556 | 72.7163 | 16.4921 | |
| | No log | 2.0 | 152 | 0.7188 | 72.4823 | 55.1403 | 72.5559 | 72.5034 | 16.5288 | |
| | No log | 3.0 | 228 | 0.7176 | 72.4979 | 55.09 | 72.5668 | 72.5151 | 16.5209 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.36.2 |
| - Pytorch 1.13.1 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
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|
