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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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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-base-finetuned-test_63829_prefix_summarize |
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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-base-finetuned-test_63829_prefix_summarize |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3498 |
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- Rouge1: 11.28 |
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- Rouge2: 3.5248 |
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- Rougel: 9.174 |
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- Rougelsum: 10.6313 |
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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: 2 |
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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: 15 |
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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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| 7.6624 | 1.25 | 500 | 2.6231 | 7.333 | 2.0471 | 6.2456 | 7.0157 | 14.01 | |
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| 3.3306 | 2.5 | 1000 | 2.5079 | 10.5135 | 3.0104 | 8.4645 | 9.8798 | 19.0 | |
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| 3.1123 | 3.75 | 1500 | 2.4512 | 10.5261 | 3.3739 | 8.6176 | 9.8711 | 19.0 | |
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| 2.9927 | 5.0 | 2000 | 2.4137 | 11.14 | 3.5973 | 9.2204 | 10.407 | 19.0 | |
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| 2.8765 | 6.25 | 2500 | 2.4050 | 10.9669 | 3.7633 | 9.1517 | 10.283 | 19.0 | |
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| 2.8211 | 7.5 | 3000 | 2.3828 | 11.6779 | 4.181 | 9.8295 | 10.9657 | 19.0 | |
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| 2.7589 | 8.75 | 3500 | 2.3756 | 11.6097 | 4.1335 | 9.7619 | 10.8368 | 19.0 | |
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| 2.722 | 10.0 | 4000 | 2.3627 | 11.8385 | 4.0634 | 9.6721 | 10.9386 | 19.0 | |
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| 2.6781 | 11.25 | 4500 | 2.3611 | 11.3415 | 3.5812 | 9.1328 | 10.6537 | 19.0 | |
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| 2.6648 | 12.5 | 5000 | 2.3524 | 11.3808 | 3.6088 | 9.2331 | 10.6316 | 19.0 | |
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| 2.6404 | 13.75 | 5500 | 2.3521 | 11.3031 | 3.5165 | 9.1629 | 10.6573 | 19.0 | |
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| 2.6397 | 15.0 | 6000 | 2.3498 | 11.28 | 3.5248 | 9.174 | 10.6313 | 19.0 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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