| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: Grammar_Summarizer |
| | 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. --> |
| |
|
| | # Grammar_Summarizer |
| | |
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5127 |
| | - Rouge1: 0.4494 |
| | - Rouge2: 0.3672 |
| | - Rougel: 0.3833 |
| | - Rougelsum: 0.3849 |
| | |
| | ## 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: 0.0005 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 16 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 90 |
| | - num_epochs: 1 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | | 2.2799 | 0.25 | 100 | 1.0334 | 0.3916 | 0.3085 | 0.2696 | 0.2717 | |
| | | 1.0618 | 0.5 | 200 | 0.6095 | 0.3287 | 0.2746 | 0.2891 | 0.2900 | |
| | | 0.8719 | 0.76 | 300 | 0.5127 | 0.4494 | 0.3672 | 0.3833 | 0.3849 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.0 |
| | |
