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--- |
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license: mit |
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base_model: facebook/mbart-large-50 |
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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: mBART-TextSimp-LT-BatchSize4-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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# mBART-TextSimp-LT-BatchSize4-lr1e-4 |
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This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0810 |
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- Rouge1: 0.8026 |
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- Rouge2: 0.6711 |
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- Rougel: 0.796 |
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- Sacrebleu: 55.7975 |
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- Gen Len: 33.3938 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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| 0.0978 | 1.0 | 209 | 0.0948 | 0.6734 | 0.5117 | 0.664 | 43.1877 | 33.3938 | |
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| 0.0617 | 2.0 | 418 | 0.0598 | 0.7702 | 0.6222 | 0.7609 | 49.5794 | 33.3938 | |
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| 1.1021 | 3.0 | 627 | 0.8158 | 0.0161 | 0.0 | 0.0162 | 0.0009 | 34.3938 | |
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| 0.0471 | 4.0 | 836 | 0.0822 | 0.6874 | 0.5335 | 0.6779 | 44.9573 | 33.3938 | |
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| 0.0276 | 5.0 | 1045 | 0.0664 | 0.7767 | 0.6339 | 0.7686 | 52.2135 | 33.3938 | |
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| 0.0162 | 6.0 | 1254 | 0.0756 | 0.7856 | 0.6452 | 0.7796 | 50.4352 | 33.3938 | |
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| 0.0069 | 7.0 | 1463 | 0.0796 | 0.7939 | 0.6586 | 0.7877 | 52.9489 | 33.3938 | |
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| 0.0051 | 8.0 | 1672 | 0.0810 | 0.8026 | 0.6711 | 0.796 | 55.7975 | 33.3938 | |
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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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