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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-lr5e-5 |
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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-lr5e-5 |
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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: 0.0720 |
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- Rouge1: 0.7898 |
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- Rouge2: 0.643 |
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- Rougel: 0.783 |
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- Sacrebleu: 57.6148 |
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- Gen Len: 33.6014 |
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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: 5e-05 |
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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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| 0.407 | 1.0 | 209 | 0.1938 | 0.6481 | 0.4813 | 0.6379 | 42.027 | 33.6014 | |
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| 0.8377 | 2.0 | 418 | 0.1076 | 0.6446 | 0.4765 | 0.632 | 40.6092 | 33.7852 | |
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| 0.0589 | 3.0 | 627 | 0.0561 | 0.7659 | 0.6056 | 0.7581 | 51.836 | 33.6014 | |
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| 0.0237 | 4.0 | 836 | 0.0551 | 0.7816 | 0.6292 | 0.774 | 54.6775 | 33.6014 | |
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| 0.009 | 5.0 | 1045 | 0.0598 | 0.78 | 0.628 | 0.7723 | 54.4212 | 33.6014 | |
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| 0.0059 | 6.0 | 1254 | 0.0648 | 0.7876 | 0.6424 | 0.7805 | 56.5662 | 33.6014 | |
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| 0.003 | 7.0 | 1463 | 0.0694 | 0.7883 | 0.6405 | 0.781 | 57.3259 | 33.6014 | |
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| 0.0013 | 8.0 | 1672 | 0.0720 | 0.7898 | 0.643 | 0.783 | 57.6148 | 33.6014 | |
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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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