| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: allenai/led-base-16384 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| - bleu |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: LED_sum_outcome |
| 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_sum_outcome |
|
|
| 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: 3.4730 |
| - Rouge1: 0.3601 |
| - Rouge2: 0.1515 |
| - Rougel: 0.3017 |
| - Rougelsum: 0.301 |
| - Gen Len: 20.36 |
| - Bleu: 0.0595 |
| - Precisions: 0.1544 |
| - Brevity Penalty: 0.6108 |
| - Length Ratio: 0.6698 |
| - Translation Length: 785.0 |
| - Reference Length: 1172.0 |
| - Precision: 0.8997 |
| - Recall: 0.8766 |
| - F1: 0.8879 |
| - Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
|
|
| ## 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: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Precision | Recall | F1 | Hashcode | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:| |
| | No log | 1.0 | 7 | 7.7628 | 0.2668 | 0.0617 | 0.2177 | 0.2179 | 21.0 | 0.0211 | 0.0856 | 0.6935 | 0.7321 | 858.0 | 1172.0 | 0.8742 | 0.86 | 0.8669 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 2.0 | 14 | 6.5648 | 0.3427 | 0.124 | 0.2806 | 0.2804 | 20.16 | 0.0514 | 0.1396 | 0.6085 | 0.6681 | 783.0 | 1172.0 | 0.8991 | 0.8717 | 0.8851 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 3.0 | 21 | 5.1851 | 0.3468 | 0.1383 | 0.282 | 0.2807 | 19.7 | 0.0722 | 0.1711 | 0.578 | 0.6459 | 757.0 | 1172.0 | 0.9029 | 0.8772 | 0.8898 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 4.0 | 28 | 4.4398 | 0.3475 | 0.1299 | 0.2825 | 0.2821 | 20.18 | 0.0455 | 0.1417 | 0.598 | 0.6604 | 774.0 | 1172.0 | 0.8979 | 0.8766 | 0.887 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 5.0 | 35 | 4.0655 | 0.3506 | 0.1412 | 0.2913 | 0.2901 | 19.94 | 0.054 | 0.1556 | 0.5685 | 0.6391 | 749.0 | 1172.0 | 0.8987 | 0.8772 | 0.8877 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 6.0 | 42 | 3.8299 | 0.356 | 0.148 | 0.295 | 0.294 | 20.38 | 0.0616 | 0.1566 | 0.6073 | 0.6672 | 782.0 | 1172.0 | 0.9002 | 0.8781 | 0.8889 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 7.0 | 49 | 3.6727 | 0.3645 | 0.144 | 0.2966 | 0.296 | 20.38 | 0.0637 | 0.1593 | 0.6108 | 0.6698 | 785.0 | 1172.0 | 0.8987 | 0.8774 | 0.8878 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 8.0 | 56 | 3.5737 | 0.3586 | 0.146 | 0.2948 | 0.2941 | 20.44 | 0.0632 | 0.1563 | 0.6201 | 0.6766 | 793.0 | 1172.0 | 0.8965 | 0.8762 | 0.8862 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 9.0 | 63 | 3.5072 | 0.3568 | 0.1486 | 0.2976 | 0.2963 | 20.36 | 0.0598 | 0.1536 | 0.6189 | 0.6758 | 792.0 | 1172.0 | 0.8986 | 0.8769 | 0.8875 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| | No log | 10.0 | 70 | 3.4730 | 0.3601 | 0.1515 | 0.3017 | 0.301 | 20.36 | 0.0595 | 0.1544 | 0.6108 | 0.6698 | 785.0 | 1172.0 | 0.8997 | 0.8766 | 0.8879 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.53.0 |
| - Pytorch 2.7.0+cu126 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
| |
