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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_30483_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_30483_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: 2.3527 |
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- Rouge1: 23.6141 |
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- Rouge2: 7.1791 |
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- Rougel: 16.0152 |
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- Rougelsum: 21.8213 |
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- Gen Len: 69.64 |
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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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| 7.4668 | 1.25 | 500 | 2.6478 | 10.4597 | 4.2457 | 8.7184 | 9.8473 | 18.49 | |
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| 3.3231 | 2.5 | 1000 | 2.5146 | 17.7315 | 6.0795 | 13.5384 | 16.6839 | 40.55 | |
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| 3.0956 | 3.75 | 1500 | 2.4512 | 20.2871 | 6.4051 | 14.8508 | 18.8768 | 51.35 | |
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| 2.9928 | 5.0 | 2000 | 2.4180 | 21.4196 | 6.629 | 15.2607 | 20.1471 | 57.92 | |
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| 2.8802 | 6.25 | 2500 | 2.4030 | 21.7949 | 6.7926 | 15.2506 | 20.338 | 61.05 | |
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| 2.8243 | 7.5 | 3000 | 2.3856 | 21.7075 | 6.7397 | 15.0044 | 20.1744 | 61.19 | |
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| 2.7646 | 8.75 | 3500 | 2.3847 | 22.4137 | 6.7644 | 14.9987 | 20.7797 | 63.81 | |
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| 2.7096 | 10.0 | 4000 | 2.3691 | 22.3403 | 6.9812 | 15.5411 | 20.6166 | 62.79 | |
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| 2.6758 | 11.25 | 4500 | 2.3612 | 23.6542 | 7.2355 | 15.9979 | 21.9807 | 69.83 | |
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| 2.6579 | 12.5 | 5000 | 2.3556 | 23.7473 | 7.5446 | 16.0314 | 21.917 | 69.75 | |
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| 2.651 | 13.75 | 5500 | 2.3557 | 23.9711 | 7.5018 | 16.2033 | 22.2811 | 69.29 | |
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| 2.639 | 15.0 | 6000 | 2.3527 | 23.6141 | 7.1791 | 16.0152 | 21.8213 | 69.64 | |
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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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