| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/mt5-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: mt5-large-ie-budquo-5k |
| 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-large-ie-budquo-5k |
|
|
| This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0504 |
| - Rouge1: 0.1024 |
| - Rouge2: 0.0848 |
| - Rougel: 0.1021 |
| - Rougelsum: 0.1023 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 4 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 0.1081 | 0.9997 | 1921 | 0.0537 | 0.0995 | 0.0819 | 0.0994 | 0.0993 | |
| | 0.0291 | 2.0 | 3843 | 0.0177 | 0.1030 | 0.0866 | 0.1030 | 0.1029 | |
| | 0.0157 | 2.9997 | 5764 | 0.0101 | 0.1041 | 0.0878 | 0.1040 | 0.1037 | |
| | 0.0092 | 4.0 | 7686 | 0.0071 | 0.1039 | 0.0881 | 0.1040 | 0.1038 | |
| | 0.0061 | 4.9987 | 9605 | 0.0067 | 0.1045 | 0.0884 | 0.1043 | 0.1041 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
| |
