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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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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-rahul-summariza |
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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-rahul-summariza |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7002 |
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- Rouge1: 29.5043 |
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- Rouge2: 23.832 |
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- Rougel: 27.5786 |
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- Rougelsum: 28.404 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 2 |
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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: 20 |
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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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| 1.123 | 1.0 | 16 | 0.8258 | 27.2788 | 21.3634 | 25.7114 | 26.7324 | 19.0 | |
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| 0.9067 | 2.0 | 32 | 0.7539 | 28.873 | 23.5401 | 27.2337 | 27.939 | 19.0 | |
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| 0.8137 | 3.0 | 48 | 0.7280 | 29.1767 | 23.6599 | 27.7065 | 28.3569 | 19.0 | |
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| 0.7872 | 4.0 | 64 | 0.7230 | 29.0451 | 23.4597 | 27.2762 | 28.1324 | 19.0 | |
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| 0.7338 | 5.0 | 80 | 0.7133 | 29.4821 | 23.8113 | 27.4912 | 28.326 | 19.0 | |
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| 0.6913 | 6.0 | 96 | 0.7101 | 29.4237 | 23.8523 | 27.4109 | 28.2418 | 19.0 | |
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| 0.6679 | 7.0 | 112 | 0.7097 | 29.4237 | 23.8523 | 27.4109 | 28.2418 | 19.0 | |
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| 0.6963 | 8.0 | 128 | 0.7046 | 29.4237 | 23.8523 | 27.4109 | 28.2418 | 19.0 | |
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| 0.6223 | 9.0 | 144 | 0.7052 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 | |
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| 0.6494 | 10.0 | 160 | 0.7019 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 | |
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| 0.616 | 11.0 | 176 | 0.7010 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 | |
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| 0.6058 | 12.0 | 192 | 0.7028 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 | |
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| 0.5964 | 13.0 | 208 | 0.6996 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 | |
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| 0.5958 | 14.0 | 224 | 0.6997 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 | |
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| 0.57 | 15.0 | 240 | 0.6996 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 | |
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| 0.5714 | 16.0 | 256 | 0.6998 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 | |
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| 0.5648 | 17.0 | 272 | 0.6999 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 | |
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| 0.5258 | 18.0 | 288 | 0.7005 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 | |
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| 0.5692 | 19.0 | 304 | 0.7001 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 | |
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| 0.5708 | 20.0 | 320 | 0.7002 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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