| --- |
| license: apache-2.0 |
| base_model: allenai/led-base-16384 |
| tags: |
| - summarization |
| - generated_from_trainer |
| model-index: |
| - name: led |
| 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 |
|
|
| 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: |
| - eval_loss: 2.5049 |
| - eval_rouge1_precision: 0.2436 |
| - eval_rouge1_recall: 0.3162 |
| - eval_rouge1_fmeasure: 0.2711 |
| - eval_runtime: 3740.5655 |
| - eval_samples_per_second: 0.802 |
| - eval_steps_per_second: 0.025 |
| - epoch: 0.13 |
| - step: 30 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
| - mixed_precision_training: Native AMP |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.14.5 |
| - Tokenizers 0.15.1 |
| |
