| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: gsarti/it5-small-news-summarization |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: news_summary_model_trained_on_reduced_data |
| 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. --> |
|
|
| # news_summary_model_trained_on_reduced_data |
|
|
| This model is a fine-tuned version of [gsarti/it5-small-news-summarization](https://huggingface.co/gsarti/it5-small-news-summarization) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: nan |
| - Rouge1: 0.1141 |
| - Rouge2: 0.0402 |
| - Rougel: 0.1005 |
| - Rougelsum: 0.1018 |
| - Generated Length: 19.0 |
|
|
| ## 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: 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: 3 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------------:| |
| | No log | 1.0 | 9 | nan | 0.1141 | 0.0402 | 0.1005 | 0.1018 | 19.0 | |
| | No log | 2.0 | 18 | nan | 0.1141 | 0.0402 | 0.1005 | 0.1018 | 19.0 | |
| | No log | 3.0 | 27 | nan | 0.1141 | 0.0402 | 0.1005 | 0.1018 | 19.0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
|
|
