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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-BatchSize2-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-BatchSize2-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: 0.0962 |
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- Rouge1: 0.76 |
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- Rouge2: 0.6246 |
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- Rougel: 0.7508 |
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- Sacrebleu: 53.9078 |
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- Gen Len: 32.9976 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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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| 0.0639 | 1.0 | 418 | 0.0779 | 0.7012 | 0.5432 | 0.6904 | 43.0798 | 32.9976 | |
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| 0.0653 | 2.0 | 836 | 0.0732 | 0.7197 | 0.5593 | 0.7091 | 44.8483 | 32.9976 | |
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| 0.0327 | 3.0 | 1254 | 0.0726 | 0.7319 | 0.5787 | 0.7206 | 47.842 | 32.9976 | |
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| 0.0168 | 4.0 | 1672 | 0.0782 | 0.7466 | 0.6031 | 0.7371 | 50.9225 | 32.9976 | |
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| 0.013 | 5.0 | 2090 | 0.0804 | 0.7507 | 0.6077 | 0.7409 | 51.8293 | 32.9976 | |
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| 0.0032 | 6.0 | 2508 | 0.0846 | 0.7606 | 0.6237 | 0.7507 | 53.5224 | 32.9976 | |
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| 0.0012 | 7.0 | 2926 | 0.0911 | 0.7597 | 0.6263 | 0.751 | 54.0182 | 32.9976 | |
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| 0.0012 | 8.0 | 3344 | 0.0962 | 0.76 | 0.6246 | 0.7508 | 53.9078 | 32.9976 | |
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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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