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--- |
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base_model: longt5_xl_summ_screen_memsum_bp_20/checkpoint-140 |
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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_memsum_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_memsum_bp_30 |
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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_memsum_bp |
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type: learn3r/summ_screen_fd_memsum_bp |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 47.1842 |
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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_memsum_bp_30 |
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This model is a fine-tuned version of [longt5_xl_summ_screen_memsum_bp_20/checkpoint-140](https://huggingface.co/longt5_xl_summ_screen_memsum_bp_20/checkpoint-140) on the learn3r/summ_screen_fd_memsum_bp dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6817 |
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- Rouge1: 47.1842 |
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- Rouge2: 18.22 |
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- Rougel: 28.4626 |
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- Rougelsum: 45.5778 |
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- Gen Len: 308.9083 |
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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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| 0.0707 | 0.97 | 14 | 2.7097 | 41.4751 | 15.5831 | 25.1976 | 39.9229 | 453.5296 | |
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| 0.0608 | 1.95 | 28 | 2.7271 | 45.691 | 17.905 | 27.9519 | 43.8787 | 387.4172 | |
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| 0.0851 | 2.99 | 43 | 3.0001 | 47.1647 | 17.8993 | 28.7561 | 45.661 | 261.5680 | |
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| 0.0697 | 3.97 | 57 | 2.9297 | 46.6892 | 17.8922 | 28.0724 | 44.8821 | 365.3047 | |
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| 0.0296 | 4.94 | 71 | 2.9017 | 44.2702 | 17.7874 | 26.7598 | 42.6857 | 440.6391 | |
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| 0.0312 | 5.98 | 86 | 3.0489 | 47.7884 | 18.1788 | 28.6688 | 46.0744 | 306.6716 | |
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| 0.0383 | 6.96 | 100 | 2.6817 | 47.1842 | 18.22 | 28.4626 | 45.5778 | 308.9083 | |
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| 0.0367 | 8.0 | 115 | 3.0245 | 45.5573 | 17.2161 | 28.0573 | 43.7772 | 227.8550 | |
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| 0.04 | 8.97 | 129 | 3.2873 | 44.0164 | 17.1682 | 26.4769 | 42.3752 | 429.8757 | |
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| 0.028 | 9.74 | 140 | 2.9815 | 46.6542 | 17.8515 | 28.146 | 45.0274 | 337.4822 | |
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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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