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README.md
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base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen_bp_only/checkpoint-210
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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_only_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_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: 40.4943
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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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# longt5_xl_summ_screen_bp_only_30
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This model
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It achieves the following results on the evaluation set:
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- Loss:
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- Rouge1:
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- Rouge2:
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- Rougel:
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- Rougelsum:
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- Gen Len:
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## Model description
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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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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 32
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- total_train_batch_size:
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- total_eval_batch_size: 32
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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: 15.0
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### Training results
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| Training Loss | Epoch | Step |
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| 0.324 | 0.97 | 14 |
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### Framework versions
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---
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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: longt5_xl_summ_screen_bp_only_30
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results: []
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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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# longt5_xl_summ_screen_bp_only_30
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.4990
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- Rouge1: 32.5815
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- Rouge2: 14.2951
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- Rougel: 22.4501
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- Rougelsum: 31.2928
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- Gen Len: 499.3107
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## Model description
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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: 15.0
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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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| 0.324 | 0.97 | 14 | 2.2376 | 40.4388 | 16.4662 | 28.0771 | 38.3405 | 246.7396 |
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| 0.2707 | 1.95 | 28 | 2.3204 | 40.2873 | 16.7641 | 27.3895 | 38.2689 | 307.3787 |
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| 0.2217 | 2.99 | 43 | 2.5281 | 31.9916 | 13.8136 | 22.1895 | 30.623 | 501.9320 |
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| 0.1776 | 3.97 | 57 | 2.7530 | 31.7535 | 13.8852 | 22.8653 | 30.3796 | 489.6183 |
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| 0.1424 | 4.94 | 71 | 2.6578 | 32.117 | 14.2141 | 22.3733 | 30.8328 | 502.1124 |
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| 0.1449 | 5.98 | 86 | 2.5508 | 35.3448 | 13.8478 | 24.9044 | 33.6108 | 357.3136 |
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| 0.1191 | 6.96 | 100 | 3.1622 | 37.2189 | 16.0076 | 25.7011 | 35.294 | 408.8669 |
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| 0.0879 | 8.0 | 115 | 2.8510 | 39.8825 | 16.8073 | 27.2428 | 37.9568 | 318.2278 |
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| 0.0899 | 8.97 | 129 | 2.9138 | 31.7139 | 13.7066 | 21.8844 | 30.5075 | 500.4053 |
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| 0.0656 | 9.95 | 143 | 3.1616 | 33.055 | 14.5841 | 22.5883 | 31.7565 | 488.1686 |
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| 0.0542 | 10.99 | 158 | 3.3630 | 43.7514 | 18.9011 | 29.9017 | 41.6887 | 198.8077 |
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| 0.0557 | 11.97 | 172 | 3.3826 | 42.3089 | 18.2735 | 29.0356 | 40.4154 | 270.9675 |
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| 0.0542 | 12.94 | 186 | 3.4408 | 40.7691 | 16.529 | 28.3999 | 38.9723 | 186.7308 |
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| 0.0596 | 13.98 | 201 | 3.5253 | 37.0037 | 15.9098 | 25.2808 | 35.3868 | 398.4704 |
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| 0.0385 | 14.61 | 210 | 3.4990 | 32.5815 | 14.2951 | 22.4501 | 31.2928 | 499.3107 |
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### Framework versions
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