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--- |
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base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen/checkpoint-140 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tau/scrolls |
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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_20 |
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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: tau/scrolls summ_screen_fd |
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type: tau/scrolls |
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config: summ_screen_fd |
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split: validation |
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args: summ_screen_fd |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 28.1708 |
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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_20 |
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This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen/checkpoint-140](https://huggingface.co.//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen/checkpoint-140) on the tau/scrolls summ_screen_fd dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1917 |
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- Rouge1: 28.1708 |
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- Rouge2: 6.6895 |
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- Rougel: 18.1637 |
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- Rougelsum: 24.3987 |
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- Gen Len: 96.2041 |
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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: 2 |
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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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| 0.4063 | 0.97 | 14 | 3.7385 | 27.9171 | 6.7215 | 17.9315 | 24.363 | 71.9083 | |
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| 0.3125 | 1.95 | 28 | 3.1917 | 28.1708 | 6.6895 | 18.1637 | 24.3987 | 96.2041 | |
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| 0.2177 | 2.99 | 43 | 3.9998 | 29.3167 | 5.9 | 17.3608 | 25.6945 | 198.0473 | |
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| 0.1753 | 3.97 | 57 | 4.2287 | 29.0605 | 6.2534 | 17.5744 | 25.6415 | 158.6509 | |
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| 0.2747 | 4.94 | 71 | 4.1027 | 31.2245 | 6.5663 | 18.1588 | 26.8996 | 118.4438 | |
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| 0.1045 | 5.98 | 86 | 5.0581 | 30.6056 | 6.8892 | 18.4933 | 26.4027 | 92.9882 | |
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| 0.0875 | 6.96 | 100 | 4.5941 | 32.5234 | 7.3736 | 18.8958 | 28.4738 | 160.8964 | |
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| 0.1572 | 8.0 | 115 | 4.9386 | 31.4658 | 7.2592 | 18.4796 | 27.6047 | 121.0178 | |
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| 0.0867 | 8.97 | 129 | 4.5565 | 32.0531 | 7.0692 | 18.5551 | 27.3373 | 160.4793 | |
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| 0.0748 | 9.74 | 140 | 5.0866 | 32.2717 | 7.7004 | 18.9107 | 28.3874 | 124.1893 | |
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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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