| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - cnn_dailymail |
| | base_model: facebook/bart-base |
| | model-index: |
| | - name: bart-cnndm |
| | 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. --> |
| |
|
| | # bart-cnndm |
| |
|
| | This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the cnn_dailymail dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.6305 |
| | |
| | ## 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: 5e-05 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 16 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 1 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 2.0521 | 0.06 | 500 | 1.8483 | |
| | | 2.0187 | 0.11 | 1000 | 1.7939 | |
| | | 1.9884 | 0.17 | 1500 | 1.7849 | |
| | | 2.0118 | 0.22 | 2000 | 1.7372 | |
| | | 1.9341 | 0.28 | 2500 | 1.7180 | |
| | | 1.8866 | 0.33 | 3000 | 1.7186 | |
| | | 1.9491 | 0.39 | 3500 | 1.6971 | |
| | | 1.8668 | 0.45 | 4000 | 1.6930 | |
| | | 1.9666 | 0.5 | 4500 | 1.6570 | |
| | | 1.9386 | 0.56 | 5000 | 1.6703 | |
| | | 1.9207 | 0.61 | 5500 | 1.6570 | |
| | | 1.876 | 0.67 | 6000 | 1.6571 | |
| | | 1.9118 | 0.72 | 6500 | 1.6541 | |
| | | 1.8098 | 0.78 | 7000 | 1.6506 | |
| | | 1.8564 | 0.84 | 7500 | 1.6391 | |
| | | 1.8527 | 0.89 | 8000 | 1.6376 | |
| | | 1.7987 | 0.95 | 8500 | 1.6324 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.1 |
| | - Pytorch 1.13.1+cu117 |
| | - Datasets 2.10.1 |
| | - Tokenizers 0.13.2 |
| | |
