| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-t5/t5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: 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. --> |
|
|
| # summarization_model |
| |
| This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.8757 |
| - Rouge1: 0.394 |
| - Rouge2: 0.166 |
| - Rougel: 0.3264 |
| - Rougelsum: 0.3263 |
| - Gen Len: 16.3055 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 389 | 1.9453 | 0.3776 | 0.1556 | 0.3135 | 0.3136 | 15.9023 | |
| | 2.2585 | 2.0 | 778 | 1.8995 | 0.3864 | 0.1602 | 0.3209 | 0.321 | 16.1286 | |
| | 2.1003 | 3.0 | 1167 | 1.8807 | 0.3926 | 0.1654 | 0.3256 | 0.3256 | 16.1897 | |
| | 2.064 | 4.0 | 1556 | 1.8757 | 0.394 | 0.166 | 0.3264 | 0.3263 | 16.3055 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
| |
