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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: switch-base-32-samsum-ba16-lr1e-04-top-4-choose-1-res-phase2-budget3-dim1 |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: samsum |
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type: samsum |
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config: samsum |
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split: validation |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 50.511 |
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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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# switch-base-32-samsum-ba16-lr1e-04-top-4-choose-1-res-phase2-budget3-dim1 |
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This model was trained from scratch on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8163 |
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- Rouge1: 50.511 |
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- Rouge2: 26.0947 |
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- Rougel: 42.4175 |
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- Rougelsum: 46.4756 |
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- Gen Len: 20.522 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5.0 |
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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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| 1.2114 | 0.5429 | 500 | 1.6695 | 49.8655 | 25.6608 | 42.0018 | 46.1475 | 20.4132 | |
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| 1.1553 | 1.0858 | 1000 | 1.7089 | 50.2875 | 25.9243 | 42.157 | 46.4898 | 22.3178 | |
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| 1.1419 | 1.6287 | 1500 | 1.6890 | 50.7227 | 26.5404 | 42.6219 | 46.9542 | 21.0575 | |
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| 1.0082 | 2.1716 | 2000 | 1.7140 | 51.0857 | 26.9422 | 42.9033 | 47.4713 | 21.6002 | |
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| 1.057 | 2.7144 | 2500 | 1.7156 | 50.6415 | 26.6621 | 42.6293 | 46.728 | 21.6333 | |
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| 0.9098 | 3.2573 | 3000 | 1.7776 | 51.1518 | 27.178 | 43.2364 | 47.3776 | 21.2433 | |
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| 0.993 | 3.8002 | 3500 | 1.7702 | 50.9856 | 26.6895 | 42.0314 | 46.9763 | 22.6919 | |
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| 0.8361 | 4.3431 | 4000 | 1.8436 | 50.4271 | 25.8178 | 42.3022 | 46.5182 | 21.9022 | |
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| 0.9078 | 4.8860 | 4500 | 1.8163 | 50.511 | 26.0947 | 42.4175 | 46.4756 | 20.522 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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