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--- |
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license: apache-2.0 |
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base_model: google/long-t5-tglobal-xl |
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tags: |
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- generated_from_trainer |
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datasets: |
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- learn3r/summ_screen_fd_bp |
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metrics: |
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- rouge |
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model-index: |
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- name: longt5_xl_summ_screen_bp_10 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: learn3r/summ_screen_fd_bp |
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type: learn3r/summ_screen_fd_bp |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 22.9554 |
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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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# longt5_xl_summ_screen_bp_10 |
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This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/summ_screen_fd_bp dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3323 |
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- Rouge1: 22.9554 |
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- Rouge2: 6.4509 |
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- Rougel: 19.7437 |
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- Rougelsum: 20.923 |
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- Gen Len: 497.2456 |
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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: 0.001 |
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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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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 10.0 |
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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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| 2.4559 | 0.97 | 14 | 2.0707 | 11.7833 | 1.6011 | 11.1858 | 10.3025 | 511.0 | |
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| 1.6238 | 1.95 | 28 | 1.5287 | 19.0489 | 4.687 | 16.6504 | 17.1808 | 511.0 | |
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| 1.3964 | 2.99 | 43 | 1.3520 | 21.9994 | 5.8519 | 18.9231 | 19.958 | 511.0 | |
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| 1.2538 | 3.97 | 57 | 1.3323 | 22.9554 | 6.4509 | 19.7437 | 20.923 | 497.2456 | |
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| 1.277 | 4.94 | 71 | 1.5462 | 14.6326 | 3.6509 | 12.4805 | 13.5001 | 507.2278 | |
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| 1.0071 | 5.98 | 86 | 1.3604 | 29.5352 | 9.9544 | 22.1073 | 28.1204 | 429.7722 | |
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| 0.8685 | 6.96 | 100 | 1.4361 | 31.0337 | 10.6724 | 22.3815 | 29.6325 | 451.7840 | |
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| 0.7498 | 8.0 | 115 | 1.5302 | 28.433 | 8.4887 | 21.3588 | 26.6817 | 473.8964 | |
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| 0.6226 | 8.97 | 129 | 1.6289 | 37.251 | 12.8214 | 24.8704 | 36.0027 | 358.7663 | |
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| 0.5558 | 9.74 | 140 | 1.5811 | 35.4657 | 12.0036 | 24.7787 | 34.3775 | 284.0266 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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