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--- |
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license: apache-2.0 |
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base_model: google/mt5-large |
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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: mt5-large-finetuned-scope-summarization |
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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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# mt5-large-finetuned-scope-summarization |
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This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 8.2775 |
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- Rouge1: 5.918 |
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- Rouge2: 1.0667 |
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- Rougel: 5.7247 |
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- Rougelsum: 5.552 |
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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: 8 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 27.8719 | 1.0 | 13 | 15.8303 | 9.9779 | 0.8912 | 8.8304 | 8.8653 | |
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| 25.4142 | 2.0 | 26 | 20.3410 | 11.3301 | 1.0662 | 9.8807 | 9.8442 | |
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| 24.8026 | 3.0 | 39 | 16.5876 | 11.1912 | 1.5008 | 9.9776 | 9.9685 | |
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| 23.7918 | 4.0 | 52 | 14.0667 | 11.5953 | 1.6391 | 10.2961 | 10.1512 | |
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| 21.945 | 5.0 | 65 | 12.3075 | 10.6522 | 1.2121 | 10.0748 | 10.0261 | |
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| 18.8588 | 6.0 | 78 | 11.8270 | 11.4944 | 1.4152 | 9.9891 | 9.9505 | |
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| 16.587 | 7.0 | 91 | 10.7425 | 9.9989 | 1.425 | 8.9661 | 8.9811 | |
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| 15.9949 | 8.0 | 104 | 10.2228 | 10.0086 | 1.6533 | 8.9911 | 9.0047 | |
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| 15.2301 | 9.0 | 117 | 11.2979 | 9.2011 | 1.425 | 8.9267 | 8.8763 | |
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| 14.9655 | 10.0 | 130 | 11.3654 | 9.3934 | 1.6533 | 8.9243 | 8.8443 | |
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| 14.7982 | 11.0 | 143 | 10.7718 | 8.5085 | 1.4133 | 8.0936 | 8.0127 | |
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| 13.5222 | 12.0 | 156 | 10.0961 | 7.849 | 1.1637 | 7.3283 | 7.1943 | |
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| 13.0959 | 13.0 | 169 | 9.4677 | 8.0846 | 1.1637 | 7.1215 | 7.0501 | |
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| 13.0554 | 14.0 | 182 | 8.9576 | 7.0454 | 1.2494 | 6.7761 | 6.6897 | |
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| 13.1098 | 15.0 | 195 | 8.7926 | 7.9192 | 1.4133 | 7.742 | 7.6718 | |
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| 12.4133 | 16.0 | 208 | 8.5472 | 7.0176 | 1.2819 | 6.8465 | 6.8276 | |
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| 12.4751 | 17.0 | 221 | 8.5494 | 5.918 | 1.0667 | 5.7247 | 5.552 | |
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| 11.9681 | 18.0 | 234 | 8.5223 | 5.918 | 1.0667 | 5.7247 | 5.552 | |
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| 11.8797 | 19.0 | 247 | 8.3327 | 5.918 | 1.0667 | 5.7247 | 5.552 | |
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| 11.8815 | 20.0 | 260 | 8.2775 | 5.918 | 1.0667 | 5.7247 | 5.552 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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