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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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- sacrebleu |
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model-index: |
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- name: mT5-TextSimp-LT-BatchSize8-lr1e-4 |
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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-TextSimp-LT-BatchSize8-lr1e-4 |
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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: 0.0826 |
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- Rouge1: 0.6956 |
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- Rouge2: 0.532 |
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- Rougel: 0.6875 |
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- Sacrebleu: 41.0349 |
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- Gen Len: 38.0501 |
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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: 0.0001 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 22.5133 | 0.96 | 200 | 14.4822 | 0.0057 | 0.0 | 0.0056 | 0.0013 | 512.0 | |
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| 1.0276 | 1.91 | 400 | 0.7352 | 0.022 | 0.0005 | 0.0215 | 0.0232 | 41.4702 | |
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| 0.6477 | 2.87 | 600 | 1.5193 | 0.1021 | 0.012 | 0.0954 | 0.0573 | 83.3723 | |
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| 0.1784 | 3.83 | 800 | 0.1149 | 0.6014 | 0.4222 | 0.5898 | 32.2723 | 38.0501 | |
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| 0.158 | 4.78 | 1000 | 0.0930 | 0.6546 | 0.4822 | 0.6463 | 37.3842 | 38.0501 | |
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| 0.1059 | 5.74 | 1200 | 0.0884 | 0.6714 | 0.4983 | 0.6635 | 39.0129 | 38.0501 | |
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| 0.1542 | 6.7 | 1400 | 0.0830 | 0.688 | 0.5184 | 0.6803 | 40.419 | 38.0501 | |
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| 0.1206 | 7.66 | 1600 | 0.0826 | 0.6956 | 0.532 | 0.6875 | 41.0349 | 38.0501 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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