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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- xlsum |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-xlsum-10-epoch |
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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: xlsum |
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type: xlsum |
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args: english |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 31.6534 |
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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-xlsum-10-epoch |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2204 |
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- Rouge1: 31.6534 |
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- Rouge2: 10.0563 |
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- Rougel: 24.8104 |
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- Rougelsum: 24.8732 |
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- Gen Len: 18.7913 |
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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: 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: 10 |
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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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| 2.6512 | 1.0 | 19158 | 2.3745 | 29.756 | 8.4006 | 22.9753 | 23.0287 | 18.8245 | |
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| 2.6012 | 2.0 | 38316 | 2.3183 | 30.5327 | 9.0206 | 23.7263 | 23.7805 | 18.813 | |
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| 2.5679 | 3.0 | 57474 | 2.2853 | 30.9771 | 9.4156 | 24.1555 | 24.2127 | 18.7905 | |
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| 2.5371 | 4.0 | 76632 | 2.2660 | 31.0578 | 9.5592 | 24.2983 | 24.3587 | 18.7941 | |
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| 2.5133 | 5.0 | 95790 | 2.2498 | 31.3756 | 9.7889 | 24.5317 | 24.5922 | 18.7971 | |
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| 2.4795 | 6.0 | 114948 | 2.2378 | 31.4961 | 9.8935 | 24.6648 | 24.7218 | 18.7929 | |
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| 2.4967 | 7.0 | 134106 | 2.2307 | 31.44 | 9.9125 | 24.6298 | 24.6824 | 18.8221 | |
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| 2.4678 | 8.0 | 153264 | 2.2250 | 31.5875 | 10.004 | 24.7581 | 24.8125 | 18.7809 | |
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| 2.46 | 9.0 | 172422 | 2.2217 | 31.6413 | 10.0311 | 24.8063 | 24.8641 | 18.7951 | |
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| 2.4494 | 10.0 | 191580 | 2.2204 | 31.6534 | 10.0563 | 24.8104 | 24.8732 | 18.7913 | |
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### Framework versions |
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- Transformers 4.13.0 |
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- Pytorch 1.13.1+cpu |
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- Datasets 2.8.0 |
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- Tokenizers 0.10.3 |
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