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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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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-xsum |
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results: [] |
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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 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3773 |
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- Rouge1: 76.5735 |
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- Rouge2: 74.0611 |
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- Rougel: 76.9279 |
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- Rougelsum: 76.7502 |
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- Gen Len: 12.3684 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 64 |
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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 | 3 | 2.3350 | 8.9016 | 4.9624 | 8.561 | 8.521 | 17.0789 | |
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| No log | 2.0 | 6 | 2.2082 | 8.8982 | 4.9624 | 8.5474 | 8.4807 | 16.8158 | |
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| No log | 3.0 | 9 | 2.0239 | 6.3522 | 2.8822 | 5.9706 | 5.9968 | 16.3947 | |
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| No log | 4.0 | 12 | 1.9026 | 6.3122 | 2.8822 | 5.7577 | 5.8666 | 16.5526 | |
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| No log | 5.0 | 15 | 1.7655 | 6.7889 | 2.8822 | 6.229 | 6.3143 | 16.3684 | |
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| No log | 6.0 | 18 | 1.6270 | 6.2127 | 3.2331 | 5.5808 | 5.6566 | 15.6579 | |
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| No log | 7.0 | 21 | 1.5019 | 6.2816 | 3.3198 | 5.6661 | 5.7835 | 15.3158 | |
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| No log | 8.0 | 24 | 1.4107 | 6.2816 | 3.3198 | 5.6661 | 5.7835 | 15.3421 | |
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| No log | 9.0 | 27 | 1.3240 | 10.8854 | 6.6397 | 10.1852 | 10.2678 | 15.4211 | |
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| No log | 10.0 | 30 | 1.2590 | 15.747 | 13.6747 | 15.9617 | 16.0821 | 15.1053 | |
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| No log | 11.0 | 33 | 1.1988 | 18.5812 | 15.8877 | 18.637 | 18.8755 | 15.0789 | |
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| No log | 12.0 | 36 | 1.1513 | 14.0714 | 11.6088 | 14.2061 | 14.0938 | 14.7632 | |
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| No log | 13.0 | 39 | 1.1108 | 16.0599 | 13.3917 | 16.225 | 15.9864 | 14.8947 | |
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| No log | 14.0 | 42 | 1.0766 | 17.8985 | 15.6223 | 18.4261 | 18.2524 | 14.9474 | |
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| No log | 15.0 | 45 | 1.0448 | 17.8985 | 15.6223 | 18.4261 | 18.2524 | 14.9474 | |
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| No log | 16.0 | 48 | 1.0137 | 17.8985 | 15.6223 | 18.4261 | 18.2524 | 14.9474 | |
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| No log | 17.0 | 51 | 0.9843 | 17.8985 | 15.6223 | 18.4261 | 18.2524 | 14.6316 | |
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| No log | 18.0 | 54 | 0.9598 | 27.5385 | 24.73 | 27.5826 | 27.7639 | 14.4474 | |
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| No log | 19.0 | 57 | 0.9313 | 28.9525 | 25.8784 | 29.148 | 29.1478 | 14.4474 | |
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| No log | 20.0 | 60 | 0.9001 | 29.7391 | 26.6691 | 30.1382 | 30.1101 | 14.4737 | |
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| No log | 21.0 | 63 | 0.8695 | 31.6294 | 28.402 | 32.1917 | 32.0891 | 14.3684 | |
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| No log | 22.0 | 66 | 0.8406 | 33.9712 | 30.7072 | 34.382 | 34.3829 | 14.3158 | |
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| No log | 23.0 | 69 | 0.8133 | 36.0319 | 32.7218 | 36.607 | 36.4543 | 14.3421 | |
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| No log | 24.0 | 72 | 0.7880 | 36.0319 | 32.7218 | 36.607 | 36.4543 | 14.3421 | |
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| No log | 25.0 | 75 | 0.7622 | 36.3979 | 33.086 | 36.905 | 36.6806 | 14.3421 | |
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| No log | 26.0 | 78 | 0.7377 | 40.1654 | 37.0379 | 40.2783 | 40.2438 | 14.2632 | |
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| No log | 27.0 | 81 | 0.7145 | 40.7528 | 37.7009 | 41.0545 | 41.0725 | 14.1316 | |
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| No log | 28.0 | 84 | 0.6912 | 40.7528 | 37.7009 | 41.0545 | 41.0725 | 14.1316 | |
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| No log | 29.0 | 87 | 0.6674 | 42.3738 | 39.5725 | 42.4529 | 42.3105 | 13.9737 | |
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| No log | 30.0 | 90 | 0.6429 | 44.7342 | 41.9521 | 44.7141 | 44.7653 | 14.1842 | |
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| No log | 31.0 | 93 | 0.6225 | 44.7342 | 41.9521 | 44.7141 | 44.7653 | 14.1842 | |
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| No log | 32.0 | 96 | 0.6045 | 44.7342 | 41.9521 | 44.7141 | 44.7653 | 14.9737 | |
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| No log | 33.0 | 99 | 0.5874 | 44.8851 | 42.3601 | 44.6841 | 44.7448 | 14.9474 | |
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| No log | 34.0 | 102 | 0.5707 | 48.0171 | 44.6572 | 48.3977 | 48.1823 | 14.3947 | |
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| No log | 35.0 | 105 | 0.5529 | 50.0598 | 46.834 | 50.0339 | 49.9161 | 14.4474 | |
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| No log | 36.0 | 108 | 0.5356 | 52.9499 | 49.369 | 53.0648 | 52.7644 | 14.5 | |
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| No log | 37.0 | 111 | 0.5203 | 52.8057 | 49.1915 | 52.9703 | 52.6609 | 14.3947 | |
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| No log | 38.0 | 114 | 0.5058 | 58.1928 | 55.6897 | 58.5269 | 58.4782 | 14.2105 | |
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| No log | 39.0 | 117 | 0.4921 | 60.7074 | 58.7889 | 60.8191 | 60.8808 | 13.7895 | |
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| No log | 40.0 | 120 | 0.4800 | 61.7875 | 59.9339 | 61.8496 | 61.7658 | 13.6842 | |
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| No log | 41.0 | 123 | 0.4698 | 61.7875 | 59.9339 | 61.8496 | 61.7658 | 13.6842 | |
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| No log | 42.0 | 126 | 0.4597 | 62.4637 | 60.7042 | 62.487 | 62.5551 | 13.5789 | |
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| No log | 43.0 | 129 | 0.4505 | 63.0021 | 61.3266 | 62.9796 | 63.0653 | 13.3158 | |
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| No log | 44.0 | 132 | 0.4442 | 63.6533 | 62.0722 | 63.7451 | 63.7313 | 13.1316 | |
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| No log | 45.0 | 135 | 0.4388 | 63.6533 | 62.0722 | 63.7451 | 63.7313 | 13.1842 | |
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| No log | 46.0 | 138 | 0.4316 | 63.6533 | 62.0722 | 63.7451 | 63.7313 | 13.1842 | |
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| No log | 47.0 | 141 | 0.4253 | 64.5396 | 63.1662 | 64.6941 | 64.7424 | 13.1053 | |
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| No log | 48.0 | 144 | 0.4194 | 65.9713 | 63.1662 | 66.2938 | 66.3228 | 13.1053 | |
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| No log | 49.0 | 147 | 0.4134 | 69.236 | 66.507 | 69.4403 | 69.4443 | 12.7368 | |
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| No log | 50.0 | 150 | 0.4078 | 69.9113 | 67.1987 | 70.0511 | 70.203 | 12.6053 | |
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| No log | 51.0 | 153 | 0.4037 | 69.9113 | 67.1987 | 70.0511 | 70.203 | 12.6053 | |
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| No log | 52.0 | 156 | 0.4001 | 69.9113 | 67.1987 | 70.0511 | 70.203 | 12.6053 | |
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| No log | 53.0 | 159 | 0.3967 | 71.6949 | 69.5145 | 72.1298 | 71.9241 | 12.5 | |
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| No log | 54.0 | 162 | 0.3933 | 71.6949 | 69.5145 | 72.1298 | 71.9241 | 12.5526 | |
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| No log | 55.0 | 165 | 0.3901 | 71.6949 | 69.5145 | 72.1298 | 71.9241 | 12.3684 | |
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| No log | 56.0 | 168 | 0.3875 | 71.6949 | 69.5145 | 72.1298 | 71.9241 | 12.3684 | |
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| No log | 57.0 | 171 | 0.3856 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 58.0 | 174 | 0.3843 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 59.0 | 177 | 0.3828 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 60.0 | 180 | 0.3811 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 61.0 | 183 | 0.3798 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 62.0 | 186 | 0.3786 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 63.0 | 189 | 0.3777 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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| No log | 64.0 | 192 | 0.3773 | 76.5735 | 74.0611 | 76.9279 | 76.7502 | 12.3684 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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