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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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- xsum |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-xsum-updated |
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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: xsum |
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type: xsum |
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config: default |
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split: validation |
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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: 33.2945 |
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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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# t5-small-finetuned-xsum-updated |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0767 |
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- Rouge1: 33.2945 |
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- Rouge2: 12.0165 |
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- Rougel: 26.9804 |
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- Rougelsum: 26.9729 |
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- Gen Len: 18.7853 |
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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: linear |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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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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| 2.5219 | 1.0 | 12753 | 2.3054 | 30.4745 | 9.435 | 24.263 | 24.2522 | 18.823 | |
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| 2.4191 | 2.0 | 25506 | 2.2385 | 31.2305 | 10.0552 | 24.9345 | 24.9254 | 18.7562 | |
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| 2.3564 | 3.0 | 38259 | 2.1961 | 31.8234 | 10.6556 | 25.6109 | 25.6023 | 18.7708 | |
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| 2.3028 | 4.0 | 51012 | 2.1692 | 32.2053 | 11.0513 | 26.0184 | 26.0056 | 18.772 | |
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| 2.2737 | 5.0 | 63765 | 2.1452 | 32.3716 | 11.1779 | 26.1423 | 26.1363 | 18.7731 | |
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| 2.2432 | 6.0 | 76518 | 2.1304 | 32.5413 | 11.2517 | 26.2119 | 26.2098 | 18.8007 | |
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| 2.2266 | 7.0 | 89271 | 2.1193 | 32.8983 | 11.5683 | 26.5995 | 26.5958 | 18.8108 | |
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| 2.1863 | 8.0 | 102024 | 2.1058 | 32.9046 | 11.6564 | 26.6466 | 26.6473 | 18.8008 | |
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| 2.1583 | 9.0 | 114777 | 2.0987 | 32.9622 | 11.7285 | 26.7161 | 26.7116 | 18.7798 | |
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| 2.1653 | 10.0 | 127530 | 2.0900 | 33.1259 | 11.8525 | 26.8461 | 26.8419 | 18.7999 | |
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| 2.1403 | 11.0 | 140283 | 2.0880 | 33.0949 | 11.8135 | 26.7863 | 26.7765 | 18.7629 | |
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| 2.1212 | 12.0 | 153036 | 2.0825 | 33.1671 | 11.8939 | 26.9072 | 26.8982 | 18.7825 | |
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| 2.1021 | 13.0 | 165789 | 2.0793 | 33.1375 | 11.9119 | 26.8466 | 26.8386 | 18.8076 | |
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| 2.0877 | 14.0 | 178542 | 2.0774 | 33.2516 | 11.9574 | 26.9391 | 26.9327 | 18.7989 | |
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| 2.0984 | 15.0 | 191295 | 2.0767 | 33.2945 | 12.0165 | 26.9804 | 26.9729 | 18.7853 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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