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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-science-papers-NIPS |
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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-science-papers-NIPS |
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This model is a fine-tuned version of [Dagar/t5-small-science-papers](https://huggingface.co/Dagar/t5-small-science-papers) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.7566 |
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- Rouge1: 15.7066 |
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- Rouge2: 2.5654 |
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- Rougel: 11.4679 |
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- Rougelsum: 14.4017 |
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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: 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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| No log | 1.0 | 318 | 5.1856 | 13.7172 | 2.0644 | 10.2189 | 12.838 | 19.0 | |
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| 5.4522 | 2.0 | 636 | 5.0383 | 15.6211 | 2.1808 | 11.3561 | 14.3054 | 19.0 | |
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| 5.4522 | 3.0 | 954 | 4.9486 | 15.1659 | 2.3308 | 11.1052 | 13.9456 | 19.0 | |
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| 5.1254 | 4.0 | 1272 | 4.8851 | 15.716 | 2.4099 | 11.4954 | 14.5099 | 19.0 | |
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| 4.9794 | 5.0 | 1590 | 4.8456 | 15.5507 | 2.4267 | 11.3867 | 14.3237 | 19.0 | |
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| 4.9794 | 6.0 | 1908 | 4.8073 | 15.8406 | 2.4254 | 11.6878 | 14.6154 | 19.0 | |
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| 4.8823 | 7.0 | 2226 | 4.7872 | 15.5554 | 2.4637 | 11.3401 | 14.3183 | 19.0 | |
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| 4.8338 | 8.0 | 2544 | 4.7680 | 15.4783 | 2.4888 | 11.3364 | 14.2031 | 19.0 | |
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| 4.8338 | 9.0 | 2862 | 4.7621 | 15.958 | 2.5662 | 11.6139 | 14.6576 | 19.0 | |
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| 4.7838 | 10.0 | 3180 | 4.7566 | 15.7066 | 2.5654 | 11.4679 | 14.4017 | 19.0 | |
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### Framework versions |
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- Transformers 4.24.0 |
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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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