| --- |
| tags: |
| - summarization |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: test |
| 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. --> |
|
|
| # test |
|
|
| This model is a fine-tuned version of [Ameer05/tokenizer-repo](https://huggingface.co/Ameer05/tokenizer-repo) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.6109 |
| - Rouge1: 54.9442 |
| - Rouge2: 45.3299 |
| - Rougel: 50.5219 |
| - Rougelsum: 53.6475 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | No log | 0.91 | 5 | 2.3705 | 53.62 | 44.3835 | 49.6135 | 52.693 | |
| | No log | 1.91 | 10 | 1.9035 | 47.478 | 37.0934 | 39.7935 | 45.1881 | |
| | No log | 2.91 | 15 | 1.7990 | 54.2488 | 45.0782 | 49.8421 | 52.7564 | |
| | No log | 3.91 | 20 | 1.7125 | 55.7903 | 46.7554 | 52.2733 | 54.9389 | |
| | 2.4456 | 4.91 | 25 | 1.6421 | 52.2279 | 43.4391 | 49.6955 | 51.2915 | |
| | 2.4456 | 5.91 | 30 | 1.6102 | 55.8598 | 47.3293 | 53.1337 | 54.8596 | |
| | 2.4456 | 6.91 | 35 | 1.6164 | 53.7902 | 44.6622 | 49.5045 | 52.2304 | |
| | 2.4456 | 7.91 | 40 | 1.6015 | 51.5597 | 42.0333 | 47.9639 | 50.1154 | |
| | 1.239 | 8.91 | 45 | 1.6067 | 53.0301 | 43.7214 | 49.0227 | 51.8109 | |
| | 1.239 | 9.91 | 50 | 1.6109 | 54.9442 | 45.3299 | 50.5219 | 53.6475 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.15.0 |
| - Pytorch 1.9.1 |
| - Datasets 2.0.0 |
| - Tokenizers 0.10.3 |
| |
