| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: facebook/bart-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: summarize_model_2 |
| | 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. --> |
| |
|
| | # summarize_model_2 |
| |
|
| | This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.9198 |
| | - Rouge1: 0.2393 |
| | - Rouge2: 0.1023 |
| | - Rougel: 0.1976 |
| | - Rougelsum: 0.2243 |
| | - Gen Len: 20.0 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - 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 | 100 | 1.9729 | 0.2374 | 0.099 | 0.1962 | 0.2216 | 20.0 | |
| | | No log | 2.0 | 200 | 1.9565 | 0.2398 | 0.1018 | 0.1972 | 0.2238 | 20.0 | |
| | | No log | 3.0 | 300 | 1.9241 | 0.2377 | 0.0991 | 0.1959 | 0.2215 | 20.0 | |
| | | No log | 4.0 | 400 | 1.9198 | 0.2393 | 0.1023 | 0.1976 | 0.2243 | 20.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.5.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
