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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- multi_news |
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metrics: |
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- rouge |
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model-index: |
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- name: multinews_model |
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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: multi_news |
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type: multi_news |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.1482 |
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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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# multinews_model |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7165 |
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- Rouge1: 0.1482 |
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- Rouge2: 0.0472 |
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- Rougel: 0.1132 |
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- Rougelsum: 0.1132 |
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- Gen Len: 19.0 |
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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: 2e-05 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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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: linear |
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- num_epochs: 12 |
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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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| No log | 1.0 | 450 | 2.8616 | 0.1388 | 0.0418 | 0.1057 | 0.1056 | 19.0 | |
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| 3.2544 | 2.0 | 900 | 2.7991 | 0.1427 | 0.0438 | 0.1089 | 0.1089 | 19.0 | |
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| 2.999 | 3.0 | 1350 | 2.7693 | 0.1449 | 0.046 | 0.1115 | 0.1114 | 19.0 | |
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| 2.958 | 4.0 | 1800 | 2.7531 | 0.1466 | 0.0462 | 0.112 | 0.1118 | 19.0 | |
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| 2.9198 | 5.0 | 2250 | 2.7431 | 0.1466 | 0.0465 | 0.112 | 0.1119 | 19.0 | |
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| 2.8838 | 6.0 | 2700 | 2.7328 | 0.1474 | 0.0461 | 0.1125 | 0.1123 | 19.0 | |
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| 2.8774 | 7.0 | 3150 | 2.7270 | 0.1477 | 0.0463 | 0.1126 | 0.1124 | 19.0 | |
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| 2.8712 | 8.0 | 3600 | 2.7226 | 0.148 | 0.0466 | 0.1128 | 0.1127 | 19.0 | |
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| 2.854 | 9.0 | 4050 | 2.7197 | 0.1479 | 0.047 | 0.1129 | 0.1128 | 19.0 | |
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| 2.8541 | 10.0 | 4500 | 2.7188 | 0.1485 | 0.0471 | 0.113 | 0.1129 | 19.0 | |
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| 2.8541 | 11.0 | 4950 | 2.7168 | 0.1483 | 0.0472 | 0.1131 | 0.1131 | 19.0 | |
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| 2.8466 | 12.0 | 5400 | 2.7165 | 0.1482 | 0.0472 | 0.1132 | 0.1132 | 19.0 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
