| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: mt5-small_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. --> |
| |
|
| | # mt5-small_summarization |
| | |
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.1774 |
| | - Rouge1: 18.2118 |
| | - Rouge2: 6.6244 |
| | - Rougel: 15.4682 |
| | - Rougelsum: 15.3942 |
| | |
| | ## 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: 5.6e-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: 8 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
| | | 17.7253 | 1.0 | 50 | 7.6921 | 6.677 | 1.1111 | 6.5586 | 6.6861 | |
| | | 9.8457 | 2.0 | 100 | 4.5604 | 12.8991 | 1.9103 | 11.2559 | 10.9036 | |
| | | 6.2403 | 3.0 | 150 | 3.9071 | 16.463 | 4.0695 | 14.3098 | 14.4065 | |
| | | 5.2032 | 4.0 | 200 | 3.4869 | 17.6601 | 4.0878 | 14.2931 | 14.2743 | |
| | | 4.8331 | 5.0 | 250 | 3.3472 | 18.5241 | 5.3312 | 15.8993 | 16.0559 | |
| | | 4.526 | 6.0 | 300 | 3.2346 | 19.0264 | 5.7839 | 15.8013 | 16.1208 | |
| | | 4.5378 | 7.0 | 350 | 3.1927 | 18.9843 | 6.992 | 16.3787 | 16.3574 | |
| | | 4.3278 | 8.0 | 400 | 3.1774 | 18.2118 | 6.6244 | 15.4682 | 15.3942 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.20.1 |
| | - Pytorch 1.12.0 |
| | - Datasets 2.3.2 |
| | - Tokenizers 0.12.1 |
| | |
