| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - cnn_dailymail | |
| model-index: | |
| - name: tst-summarization | |
| 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. --> | |
| # tst-summarization | |
| This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the cnn_dailymail 3.0.0 dataset. | |
| It achieves the following results on the evaluation set: | |
| - eval_loss: 2.7113 | |
| - eval_rouge1: 25.387 | |
| - eval_rouge2: 9.0306 | |
| - eval_rougeL: 17.5963 | |
| - eval_rougeLsum: 22.0487 | |
| - eval_gen_len: 27.1017 | |
| - eval_runtime: 6327.8863 | |
| - eval_samples_per_second: 2.113 | |
| - eval_steps_per_second: 1.056 | |
| - step: 0 | |
| ## 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: 2 | |
| - eval_batch_size: 2 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Framework versions | |
| - Transformers 4.28.0 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |