| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: allenai/led-base-16384 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: led_model |
| 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. --> |
|
|
| # led_model |
| |
| This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4363 |
| - Rouge1: 0.7117 |
| - Rouge2: 0.5663 |
| - Rougel: 0.684 |
| - Rougelsum: 0.6843 |
| - Gen Len: 15.7955 |
| |
| ## 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 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - 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 | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 0.6184 | 0.9995 | 546 | 0.4788 | 0.699 | 0.5474 | 0.6691 | 0.6694 | 15.7362 | |
| | 0.4523 | 1.9991 | 1092 | 0.4435 | 0.7029 | 0.5569 | 0.6773 | 0.6773 | 15.6763 | |
| | 0.3732 | 2.9986 | 1638 | 0.4392 | 0.7104 | 0.565 | 0.6826 | 0.6827 | 15.8442 | |
| | 0.3249 | 3.9982 | 2184 | 0.4363 | 0.7117 | 0.5663 | 0.684 | 0.6843 | 15.7955 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
|
|
