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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: google/long-t5-tglobal-base |
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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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model-index: |
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- name: my_awesome_dailymail_long_model |
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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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# my_awesome_dailymail_long_model |
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This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6759 |
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- Rouge1: 0.2345 |
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- Rouge2: 0.0986 |
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- Rougel: 0.1918 |
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- Rougelsum: 0.1921 |
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- Gen Len: 18.999 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 2.5452 | 0.5 | 500 | 1.7971 | 0.227 | 0.0911 | 0.1815 | 0.1815 | 18.9695 | |
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| 2.2571 | 1.0 | 1000 | 1.7336 | 0.2315 | 0.0941 | 0.1865 | 0.1865 | 18.995 | |
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| 2.1671 | 1.5 | 1500 | 1.7149 | 0.2322 | 0.0958 | 0.1885 | 0.1887 | 18.995 | |
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| 2.1123 | 2.0 | 2000 | 1.6973 | 0.2343 | 0.0967 | 0.1903 | 0.1904 | 18.999 | |
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| 2.0778 | 2.5 | 2500 | 1.6900 | 0.2349 | 0.0974 | 0.1913 | 0.1914 | 18.999 | |
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| 2.0609 | 3.0 | 3000 | 1.6833 | 0.2342 | 0.098 | 0.1914 | 0.1916 | 18.999 | |
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| 2.0466 | 3.5 | 3500 | 1.6780 | 0.2344 | 0.0983 | 0.1918 | 0.192 | 18.999 | |
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| 2.0454 | 4.0 | 4000 | 1.6759 | 0.2345 | 0.0986 | 0.1918 | 0.1921 | 18.999 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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