| --- |
| license: apache-2.0 |
| base_model: allenai/led-base-16384 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - scientific_papers |
| model-index: |
| - name: allenai/led-base-16384 |
| 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. --> |
|
|
| # allenai/led-base-16384 |
|
|
| This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the scientific_papers dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.7667 |
| - Rouge2 Precision: 0.15 |
| - Rouge2 Recall: 0.0913 |
| - Rouge2 Fmeasure: 0.1075 |
| |
| ## 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: 4 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | 2.8931 | 0.32 | 10 | 2.9211 | 0.1243 | 0.1206 | 0.1119 | |
| | 3.0026 | 0.64 | 20 | 2.8150 | 0.1589 | 0.1102 | 0.1241 | |
| | 2.7651 | 0.96 | 30 | 2.7667 | 0.15 | 0.0913 | 0.1075 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.36.0 |
| - Pytorch 2.0.0 |
| - Datasets 2.1.0 |
| - Tokenizers 0.15.0 |
|
|
