| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: finetuning-summarization-model |
| | 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. --> |
| |
|
| | # finetuning-summarization-model |
| |
|
| | This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.3028 |
| | - Rouge1: 29.1184 |
| | - Rouge2: 21.1309 |
| | - Rougel: 28.3412 |
| | - Rougelsum: 28.4871 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 4 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
| | | 6.821 | 1.0 | 450 | 1.7464 | 31.7328 | 21.1788 | 30.3949 | 30.5202 | |
| | | 2.1307 | 2.0 | 900 | 1.4939 | 31.3208 | 22.0215 | 30.2589 | 30.3872 | |
| | | 1.7915 | 3.0 | 1350 | 1.4322 | 28.7824 | 19.472 | 27.926 | 28.2177 | |
| | | 1.6186 | 4.0 | 1800 | 1.3830 | 29.2568 | 20.6076 | 28.4825 | 28.6486 | |
| | | 1.5148 | 5.0 | 2250 | 1.3504 | 29.308 | 21.0698 | 28.4755 | 28.6885 | |
| | | 1.427 | 6.0 | 2700 | 1.3177 | 29.0294 | 20.706 | 28.271 | 28.3385 | |
| | | 1.3793 | 7.0 | 3150 | 1.3172 | 28.9276 | 20.922 | 28.1795 | 28.3241 | |
| | | 1.3536 | 8.0 | 3600 | 1.3028 | 29.1184 | 21.1309 | 28.3412 | 28.4871 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.1 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 2.11.0 |
| | - Tokenizers 0.13.3 |
| |
|
