| | --- |
| | license: apache-2.0 |
| | base_model: allenai/led-base-16384 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | model-index: |
| | - name: Long_attention_Longformer |
| | 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. --> |
| |
|
| | # Long_attention_Longformer |
| |
|
| | 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: 1.8677 |
| | - Bleu: 20.8728 |
| | - Meteor: 0.4023 |
| | - Comet: 0.4747 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Comet | |
| | |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:| |
| | | 2.2865 | 0.9994 | 786 | 2.1788 | 13.5745 | 0.2981 | 0.3646 | |
| | | 2.0517 | 2.0 | 1573 | 1.8939 | 19.3520 | 0.3838 | 0.4486 | |
| | | 1.9429 | 2.9981 | 2358 | 1.8313 | 20.8728 | 0.4023 | 0.4747 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.19.1 |
| | |
