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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: allenai/led-base-16384 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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- bleu |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: LED_sum_challenge |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# LED_sum_challenge |
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.8042 |
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- Rouge1: 0.2495 |
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- Rouge2: 0.0724 |
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- Rougel: 0.1912 |
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- Rougelsum: 0.192 |
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- Gen Len: 20.5 |
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- Bleu: 0.0232 |
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- Precisions: 0.0926 |
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- Brevity Penalty: 0.6016 |
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- Length Ratio: 0.6631 |
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- Translation Length: 801.0 |
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- Reference Length: 1208.0 |
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- Precision: 0.8797 |
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- Recall: 0.8676 |
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- F1: 0.8736 |
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- Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:| |
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| No log | 1.0 | 7 | 8.1739 | 0.2255 | 0.0527 | 0.1686 | 0.1688 | 21.0 | 0.0157 | 0.069 | 0.6607 | 0.707 | 854.0 | 1208.0 | 0.8668 | 0.8574 | 0.862 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 2.0 | 14 | 6.9457 | 0.2251 | 0.0588 | 0.1702 | 0.1685 | 20.7 | 0.0171 | 0.0737 | 0.6408 | 0.6921 | 836.0 | 1208.0 | 0.8737 | 0.8597 | 0.8666 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 3.0 | 21 | 5.4862 | 0.2391 | 0.0632 | 0.181 | 0.1805 | 20.52 | 0.021 | 0.0825 | 0.6431 | 0.6937 | 838.0 | 1208.0 | 0.8798 | 0.862 | 0.8708 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 4.0 | 28 | 4.7435 | 0.243 | 0.0758 | 0.1901 | 0.1892 | 20.72 | 0.0266 | 0.0886 | 0.6095 | 0.6689 | 808.0 | 1208.0 | 0.8775 | 0.8662 | 0.8717 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 5.0 | 35 | 4.3805 | 0.2557 | 0.0788 | 0.1924 | 0.1921 | 20.48 | 0.0248 | 0.1003 | 0.5857 | 0.6515 | 787.0 | 1208.0 | 0.8811 | 0.8686 | 0.8747 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 6.0 | 42 | 4.1441 | 0.2485 | 0.0701 | 0.1886 | 0.1894 | 20.52 | 0.0209 | 0.0929 | 0.5982 | 0.6606 | 798.0 | 1208.0 | 0.8816 | 0.868 | 0.8747 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 7.0 | 49 | 3.9952 | 0.2574 | 0.0713 | 0.1994 | 0.1997 | 20.54 | 0.0213 | 0.0954 | 0.6073 | 0.6672 | 806.0 | 1208.0 | 0.8811 | 0.8689 | 0.8749 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 8.0 | 56 | 3.8994 | 0.2524 | 0.067 | 0.192 | 0.192 | 20.58 | 0.0203 | 0.0908 | 0.614 | 0.6722 | 812.0 | 1208.0 | 0.8782 | 0.8675 | 0.8727 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 9.0 | 63 | 3.8355 | 0.2512 | 0.0676 | 0.1917 | 0.1925 | 20.54 | 0.0201 | 0.0901 | 0.6062 | 0.6664 | 805.0 | 1208.0 | 0.8793 | 0.8681 | 0.8736 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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| No log | 10.0 | 70 | 3.8042 | 0.2495 | 0.0724 | 0.1912 | 0.192 | 20.5 | 0.0232 | 0.0926 | 0.6016 | 0.6631 | 801.0 | 1208.0 | 0.8797 | 0.8676 | 0.8736 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) | |
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### Framework versions |
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- Transformers 4.53.0 |
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- Pytorch 2.7.0+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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