| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: sshleifer/distilbart-cnn-12-6 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: distilbart-summarization-down |
| | 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. --> |
| |
|
| | # distilbart-summarization-down |
| |
|
| | This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.0211 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 8 |
| | - optimizer: Use adafactor and the args are: |
| | No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 2.0 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 1.1316 | 0.3765 | 2000 | 1.0441 | |
| | | 1.1189 | 0.7529 | 4000 | 1.0305 | |
| | | 1.0552 | 1.1293 | 6000 | 1.0249 | |
| | | 1.021 | 1.5058 | 8000 | 1.0229 | |
| | | 1.0382 | 1.8823 | 10000 | 1.0211 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.47.0 |
| | - Pytorch 2.5.1+cu121 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
